#Self-supervised Learning Market Report

[industrynewsupdates]

Self-supervised Learning Market Growth: A Deep Dive Into Trends and Insights

The global self-supervised learning market size is estimated to reach USD 89.68 billion by 2030, expanding at a CAGR of 35.2% from 2025 to 2030, according to a new report by Grand View Research, Inc. Self-supervised learning is a machine learning technique used prominently in Natural Language Processing (NLP), followed by computer vision and speech processing applications. Applications of self-supervised learning include paraphrasing, colorization, and speech recognition. 

The COVID-19 pandemic had a positive impact on the market. More businesses adopted AI and Machine Learning as a response to the COVID-19 pandemic. Many prominent market players such as U.S.-based Amazon Web Services, Inc., Google, and Microsoft witnessed a rise in revenue during the pandemic. Moreover, accelerated digitalization also contributed to the adoption of self-supervised learning applications. For instance, in April 2020, Google Cloud, a business segment of Google, launched an Artificial Intelligence (AI) chatbot that provides critical information to fight the COVID-19 pandemic.

Many market players offer solutions for various applications such as text-to-speech and language translation & prediction. Moreover, these players are researching in self-supervised learning. For instance, U.S.-based Meta has been advancing in self-supervised learning research and has developed various algorithms and models. In February 2022, Meta announced new advances in the company’s self-supervised computer vision model SEER. The model is more powerful and is expected to enable the company in building computer vision products. 

Request Free Sample PDF of Self-supervised Learning Market Size, Share & Trends Analysis Report

Self-supervised Learning Market Report Highlights

• In terms of end-use, the BFSI segment accounted for the largest revenue share of 18.3% in 2024 and is expected to retain its position over the forecast period. This can be attributed to the increasing adoption of technologies such as AI and ML in the segment. The Advertising & Media segment is anticipated to register lucrative growth over the forecast period.

• Based on technology, the natural language processing segment accounted for the dominant share in 2024 due to its ability to handle vast amounts of unstructured text data across multiple industries.. This can be attributed to the variety and penetration of NLP applications.

• North America held the largest share of 35.7% in 2024 and is expected to retain its position over the forecast period. This can be attributed to the presence of a large number of market players in the region. Moreover, the presence of specialists and developed technology infrastructure are aiding the growth of the market.

• In July 2024, Google LLC launched the Agricultural Landscape Understanding (ALU) tool in India, an AI-based platform that uses high-resolution satellite imagery and machine learning to provide detailed insights on drought preparedness, irrigation, and crop management at an individual farm level.

• In May 2024, Researchers from Meta AI, Google, INRIA, and University Paris Saclay created an automatic dataset curation technique for self-supervised learning (SSL) using embedding models and hierarchical k-means clustering. This method improves model performance by ensuring balanced datasets and reducing the costs and time associated with manual curation.

Self-supervised Learning Market Segmentation

Grand View Research has segmented the global Self-supervised Learning market based on application and region:

Self-supervised Learning End Use Outlook (Revenue, USD Million, 2018 - 2030)

• Healthcare

• BFSI

• Automotive & Transportation

• Software Development (IT)

• Advertising & Media

• Others

Self-supervised Learning Technology Outlook (Revenue, USD Million, 2018 - 2030)

• Natural Language Processing (NLP)

• Computer Vision

• Speech Processing

Self-supervised Learning Regional Outlook (Revenue, USD Million, 2018 - 2030)

• North America

o U.S.

o Canada

o Mexico

• Europe

o UK

o Germany

o France

• Asia Pacific

o China

o Japan

o India

o Australia

o South Korea

• Latin America

o Brazil

• Middle East & Africa (MEA)

o KSA

o UAE

o South Africa

List of Key Players in Self-supervised Learning Market

• Amazon Web Services, Inc.

• Apple Inc.

• Baidu, Inc.

• Dataiku

• Databricks

• DataRobot, Inc.

• IBM Corporation

• Meta

• Microsoft

• SAS Institute Inc.

• Tesla

• The MathWorks, Inc.

Order a free sample PDF of the Self-supervised Learning Market Intelligence Study, published by Grand View Research.

[blogchaindeveloper]

AI Sales Agents

In the ever-evolving landscape of technology, artificial intelligence is no longer a futuristic concept—it’s a present-day force reshaping how professionals work, communicate, and innovate. One of the most transformative developments in this field is the rise of AI agents—intelligent systems designed to operate autonomously, collaborate with humans, and complete complex tasks across industries. These agents are becoming indispensable tools for professionals, offering efficiency, accuracy, and innovation at scale.

For those looking to leverage this emerging technology in their careers, educational credentials such as the Certified Agentic AI Expert™, Certified Agentic AI Developer™, AI Course, Gen AI Course, ChatGPT Course, and Blockchain Certification are paving the way for deep understanding and practical application.

What Are AI Agents?

AI agents are software programs equipped with the ability to perceive their environment, interpret goals, plan actions, execute tasks, and learn from outcomes—all with minimal human supervision. Unlike traditional AI systems that rely on specific commands or narrow tasks, AI agents can operate in dynamic environments, solve problems proactively, and make decisions in real time.

Whether it's managing emails, summarizing documents, scheduling meetings, analyzing financial reports, or writing code, AI agents can serve as digital assistants that not only perform routine tasks but also adapt and improve over time.

Why Professionals Are Turning to AI Agents

Professionals across industries—whether in finance, marketing, law, healthcare, or tech—are increasingly embracing AI agents for several reasons:

Time-Saving Automation: AI agents handle repetitive and administrative tasks, freeing up time for strategic thinking.

Data-Driven Decision Making: Agents can analyze massive datasets, extract insights, and present actionable recommendations in seconds.

Scalability: Unlike human teams that scale with headcount, AI agents scale with code—enabling one individual to do the work of many.

24/7 Availability: AI agents don’t sleep, take breaks, or need vacation—making them ideal for global businesses that operate across time zones.

Core Capabilities of AI Agents

Natural Language Understanding:

Many agents are powered by large language models (LLMs), like OpenAI’s GPT or Google’s Gemini, allowing them to understand and generate human language fluently. This makes them ideal for tasks like drafting emails, responding to queries, and summarizing long-form content.

Multi-Step Reasoning:

Unlike basic chatbots, modern AI agents can reason through multi-step problems. For example, a legal assistant agent could review a contract, identify risk clauses, cross-reference regulatory guidelines, and draft revisions.

Tool Integration:

AI agents can be programmed to use tools like web browsers, spreadsheets, APIs, and databases. This allows them to go beyond static responses and perform actions—booking appointments, sending reports, or pulling data from external systems.

Memory and Personalization:

Some agents are equipped with memory modules that allow them to remember user preferences, prior interactions, and contextual details. This enables more personalized and efficient workflows over time.

Self-Improvement:

Through feedback and training loops, AI agents can refine their behavior, improve accuracy, and adapt to changing environments—similar to how humans learn from experience.

Real-World Applications by Role

Marketers use AI agents to generate social media content, analyze campaign performance, and automate customer segmentation.

Lawyers deploy agents to review case files, extract legal precedents, and draft initial versions of legal documents.

Doctors and medical researchers benefit from AI agents that summarize medical journals, flag anomalies in patient records, or suggest treatment options.

Financial analysts rely on AI agents to monitor markets, forecast trends, and create dynamic reports for clients.

Software developers can delegate bug tracking, documentation, and even code writing to intelligent agents.

Building and Managing AI Agents: Training & Credentials

To work effectively with AI agents—or build your own—it’s essential to acquire the right training. Here are some key credentials that provide the necessary skills:

Certified Agentic AI Expert™:

Ideal for business leaders, strategists, and consultants, this certification focuses on understanding agentic systems, ethical frameworks, AI governance, and implementation strategies across sectors.

Certified Agentic AI Developer™:

Geared toward developers and technical professionals, this program offers hands-on training in building autonomous AI systems. It includes working with Python, LLMs, APIs, and frameworks like LangChain to develop production-ready agents.

AI Course (Fundamentals to Advanced):

A general-purpose course for beginners or professionals, covering everything from machine learning basics to advanced neural networks and deployment strategies.

Gen AI Course (Generative AI):

Specializes in using AI to create content, images, text, and code. Professionals in creative, marketing, and media fields benefit enormously from these skills.

ChatGPT Course:

Focused on prompt engineering, fine-tuning, and deploying GPT-based systems for customer support, knowledge management, and task automation.

Blockchain Certification:

As AI agents increasingly interact with decentralized platforms, a blockchain certification helps professionals understand how to integrate agents with smart contracts, decentralized identity systems, and secure data layers.

Challenges and Considerations

While AI agents offer substantial benefits, they also come with challenges:

Ethical Use: It’s vital to ensure that AI agents act within legal and ethical boundaries—especially in sensitive industries like healthcare or finance.

Security: Since agents often access sensitive data, robust cybersecurity and access controls are a must.

Bias and Fairness: Developers must be vigilant about bias in training data and ensure fairness in decision-making processes.

Oversight: Professionals should treat AI agents as collaborators, not replacements. Human oversight is crucial for quality control and strategic alignment.

Final Thoughts

AI agents are transforming the professional world—not by replacing humans, but by augmenting their capabilities. As organizations look for faster, smarter, and more adaptive ways to operate, the demand for intelligent agents—and those who can build and manage them—is surging.

Whether you're a beginner exploring an AI course, enhancing your creative edge through a Gen AI course, diving deep with a ChatGPT course, or specializing through a Certified Agentic AI Expert™, Certified Agentic AI Developer™, or Blockchain Certification, there’s never been a better time to integrate AI agents into your professional journey.

The workplace of the future will be built not just by humans, but by teams of humans and AI agents working side by side. And the professionals who master this collaboration will lead the way.

[alinashofi555]

Unlocking the Future of Finance with AI Crypto Price Prediction

Cryptocurrency markets have long been known for their volatility and unpredictability. Investors and traders alike are constantly seeking tools that can give them an edge. Enter AI crypto price prediction—an emerging technology that uses artificial intelligence to forecast price movements in digital assets. As AI continues to reshape industries, it's proving to be a game-changer in the world of crypto trading.

In this article, we’ll dive into how AI is applied to predict crypto prices, the technology behind it, its current limitations, and what the future may hold.

Why Predicting Crypto Prices Is So Challenging

Before we explore how AI helps with crypto predictions, it’s important to understand why forecasting prices in this market is particularly difficult. Cryptocurrency markets are influenced by a broad spectrum of factors:

Extreme volatility caused by speculative trading

Lack of regulatory uniformity

Global news and social media sentiment

Technical issues like network congestion or hard forks

Whale movements and low liquidity in certain tokens

Unlike traditional assets, cryptocurrencies don’t have earnings reports, dividends, or other financial indicators that help in valuation. This is where machine learning and AI step in—to fill the gap and analyze patterns humans can’t easily detect.

What Is AI Crypto Price Prediction?

AI crypto price prediction involves using artificial intelligence models, such as neural networks and deep learning algorithms, to analyze historical and real-time data and make forecasts about future price movements. These systems are built to learn from complex datasets and improve their performance over time.

Rather than relying on simple indicators like RSI or moving averages, AI models consider a variety of signals:

Historical price and volume data

Blockchain metrics like hash rate and wallet activity

Market sentiment from social media and news headlines

Macroeconomic indicators

Technical indicators, integrated into more advanced frameworks

Some platforms even incorporate natural language processing (NLP) to understand public mood based on tweets, Reddit threads, and news stories.

How AI Models Work

Most AI models used for predicting crypto prices fall into a few categories:

1. Supervised Learning

These models are trained using labeled datasets where the expected output (like price at time t+1) is known. They learn to predict future values based on input features like price trends, volume, and sentiment scores.

2. Unsupervised Learning

These models cluster data or detect anomalies without a predefined target. Useful for detecting outliers or significant market shifts.

3. Reinforcement Learning

A more experimental but powerful approach where an AI "agent" learns how to make profitable trades by interacting with a simulated market environment.

Tools and Platforms Using AI for Crypto

Several fintech startups and crypto analytics firms are already deploying AI crypto price prediction tools. Here are a few examples:

Santiment: Offers behavior analytics and on-chain signals driven by AI.

IntoTheBlock: Provides AI-based analysis of crypto assets including holders, transactions, and volatility.

Fetch.ai: A decentralized AI network that enables autonomous agents for trading and data sharing.

HaasOnline: Offers customizable AI bots for crypto trading.

These platforms aim to give users an analytical edge—highlighting when markets are likely to move, in which direction, and with what momentum.

Pros of AI in Crypto Trading

There are several benefits of using AI for predicting crypto prices:

Speed & Efficiency: AI models can process millions of data points in seconds, reacting faster than human traders.

Reduced Emotional Bias: AI doesn’t suffer from fear, greed, or FOMO. It sticks to data.

Scalable Analysis: AI can monitor hundreds of assets across multiple time frames simultaneously.

Self-Improving Systems: Many AI models are designed to learn from new data and improve over time.

These strengths make AI an increasingly popular tool for traders looking for reliable insights in an unpredictable market.

Pitfalls and Limitations

Despite the promise, AI crypto price prediction isn't flawless. Some of the biggest challenges include:

Overfitting: AI models trained too closely on past data might not perform well in real-world conditions.

Garbage In, Garbage Out: If the input data is poor or biased, the prediction will be too.

Black Box Nature: Many deep learning models offer little transparency, making it difficult to understand why a prediction was made.

Market Disruptions: Unexpected events—like a regulatory crackdown or exchange hack—can instantly make predictions invalid.

AI should be viewed as a support tool rather than a magic wand. It works best when combined with solid risk management and trading experience.

The Future of AI in Crypto Markets

The future of AI in the crypto space is bright and multifaceted. As blockchain and AI converge, we’re likely to see:

Decentralized AI protocols that offer prediction services on-chain

Smart contracts using AI to trigger actions based on price predictions

Hybrid AI-human investment teams, where analysts collaborate with intelligent models

Personalized trading bots tailored to individual risk profiles and goals

Regulations may also evolve to ensure transparency and accountability for AI-driven decisions, especially in financial markets.

Final Thoughts

AI is changing the way we understand and interact with crypto markets. By offering fast, data-driven insights, AI crypto price prediction tools are helping traders and investors make better-informed decisions. While they’re not perfect, their capabilities are improving rapidly.

As with any investment tool, it's important to do your own research, understand the limitations of the technology, and avoid over-relying on predictions. But one thing is clear: AI is no longer just a buzzword—it’s a vital part of the future of crypto trading.

[techtose]

How AI Works: Key Concepts Behind Artificial Intelligence Development

In today’s rapidly evolving digital world, Artificial Intelligence (AI) has emerged as a transformative force reshaping industries, businesses, and everyday life. But how does AI actually work? What powers the smart systems that automate tasks, analyze big data, and mimic human intelligence?

At TechTose, one of India’s leading AI development companies, we specialize in building personalized AI solutions that help businesses automate repetitive tasks, optimize operations, and unlock growth opportunities. In this blog, we break down the key concepts behind AI development and how these systems are built from the ground up.

🧠 What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and make decisions. AI systems are capable of performing tasks such as speech recognition, problem-solving, pattern detection, decision-making, and even creativity.

🔑 Key Concepts Behind AI Development

To understand how AI works, let’s explore the core components and technologies that drive AI systems:

1. Data Collection and Preparation

AI starts with data—the fuel that drives intelligent behavior.

AI systems learn from historical data.

Data is collected, cleaned, labeled, and formatted for training.

The better the quality and volume of data, the more accurate the AI output.

At TechTose, we help clients collect and structure their business data for meaningful AI integration.

2. Machine Learning (ML)

Machine Learning is a subset of AI where machines learn from data without being explicitly programmed.

Supervised Learning: AI is trained using labeled datasets (e.g., email spam detection).

Unsupervised Learning: AI identifies patterns from unlabeled data (e.g., customer segmentation).

Reinforcement Learning: AI learns by trial and error through rewards and penalties (e.g., game-playing bots).

3. Neural Networks and Deep Learning

AI systems often use Artificial Neural Networks (ANNs)—algorithms inspired by the human brain.

These networks can analyze complex data like images, speech, and text.

Deep Learning, a type of neural network with many layers, powers advanced applications like facial recognition, self-driving cars, and language models.

4. Natural Language Processing (NLP)

NLP enables machines to understand, interpret, and respond to human language.

Used in chatbots, virtual assistants, sentiment analysis, and translation tools.

TechTose develops smart NLP solutions for customer support, HR automation, and knowledge management systems.

5. Computer Vision

Computer Vision allows machines to interpret visual data from the world.

Used in applications like face recognition, object detection, medical image analysis, and automated surveillance.

At TechTose, we build custom computer vision models for quality control, security, and retail analytics.

6. Training and Optimization

Once the model is created:

It’s trained using data.

Performance is evaluated using metrics like accuracy, precision, and recall.

The model is fine-tuned until it meets the desired accuracy.

Our AI experts at TechTose ensure each solution is trained to perform optimally in real-world business scenarios.

7. Deployment and Automation

After training, AI models are integrated into applications:

Deployed via APIs, mobile apps, or enterprise software.

Monitored continuously to adapt and improve over time.

Automates workflows like report generation, customer interaction, and data analysis.

We provide end-to-end AI deployment for businesses looking to scale and streamline their operations.

🤖 Real-World Applications of AI

Here’s how businesses are using AI today:

E-commerce: Personalized product recommendations.

Healthcare: Disease prediction and diagnosis.

Finance: Fraud detection and credit scoring.

Manufacturing: Predictive maintenance.

Marketing: Customer behavior analysis.

At TechTose, we’ve worked with companies across industries to develop smart AI tools that deliver measurable results.

🚀 Why Choose TechTose for AI Development?

As a smart AI development company based in India, TechTose stands out for its commitment to delivering personalized AI solutions that solve real-world business problems. We believe that one-size-fits-all doesn't work in automation, which is why we take the time to understand your processes, data, and goals before building a solution.

Whether you need a predictive model to forecast trends, a chatbot to streamline customer support, or a computer vision system to monitor quality, our expert team at TechTose uses the latest technologies to develop scalable and secure AI systems tailored to your business needs.

We offer:

✅ Custom AI Model Development with industry-specific insights

✅ Seamless AI integration into your existing apps and infrastructure

✅ Data preparation & training support for better model accuracy

✅ Ongoing maintenance, performance tracking, and optimization

✅ Ethical AI practices that ensure fairness, privacy, and control

From startups to large enterprises, companies trust TechTose to automate tasks, reduce costs, and enhance productivity through intelligent AI solutions.

🧩 Final Thoughts

Artificial Intelligence isn’t just a futuristic buzzword—it’s a practical tool that, when developed and applied properly, can revolutionize how you do business. By understanding how AI works and leveraging expert support, companies can move faster, work smarter, and stay ahead of the curve.

Ready to automate your business with AI? Let TechTose build your next smart solution.

👉 Contact Us Today for a Free Consultation.

[vishnupriya1234]

How to Succeed as a Remote Data Analyst: Skills and Best Practices

The rise of remote work has made data analytics more accessible to professionals worldwide. While working remotely as a data analyst offers flexibility and the ability to collaborate with global teams, it also requires discipline, the right skill set, and effective work habits. To succeed in a remote data analyst role, professionals must master key technical skills, improve communication, and adopt best practices for productivity and collaboration. This blog explores essential skills and strategies for excelling as a remote data analyst from the best Data Analytics Online Training.

Essential Skills for Remote Data Analysts

A successful remote data analyst must be proficient in key technical skills that enable them to collect, clean, and analyze data efficiently. Strong expertise in SQL is crucial, as it allows analysts to query databases and extract meaningful insights. Knowledge of programming languages such as Python or R is also essential, especially for advanced statistical analysis and automation.

Data visualization is another critical skill, as analysts must present findings in a clear and engaging manner. Proficiency in tools like Tableau, Power BI, or Looker helps convey insights effectively to business teams. Additionally, familiarity with cloud platforms such as Google Cloud, AWS, or Microsoft Azure is beneficial for accessing and managing remote datasets.

Beyond technical abilities, remote data analysts must develop strong problem-solving and critical-thinking skills. The ability to interpret data and derive actionable insights is what sets successful analysts apart. Moreover, time management and self-discipline are essential for maintaining productivity without direct supervision. If you want to learn more about Data Analytics, consider enrolling in an Best Online Training & Placement programs . They often offer certifications, mentorship, and job placement opportunities to support your learning journey.

Best Practices for Succeeding as a Remote Data Analyst

To excel in a remote data analyst role, professionals must adopt effective work habits. One of the most important aspects is setting up a dedicated workspace free from distractions. Having a structured daily routine, setting clear goals, and prioritizing tasks help maintain focus and productivity.

Regular communication with team members is crucial for remote success. Since data analysts work closely with business teams, finance departments, and marketing professionals, maintaining clear communication through emails, virtual meetings, and collaboration tools like Slack or Microsoft Teams is essential. Providing detailed documentation and reports ensures that stakeholders understand the insights presented.

Another best practice is continuous learning. The field of data analytics is constantly evolving, and staying updated with new technologies, industry trends, and best practices is important for career growth. Enrolling in online courses, participating in data challenges, and joining professional networks help remote analysts stay competitive in the job market.

Overcoming Challenges in Remote Data Analytics

While remote work offers flexibility, it also presents challenges that data analysts must overcome. One common difficulty is the lack of immediate support from colleagues. Unlike office settings where analysts can quickly ask for help, remote work requires more independence and problem-solving skills. Engaging in online forums, professional communities, and virtual mentorship programs can help bridge this gap.

Another challenge is ensuring data security and compliance. Since remote analysts work with sensitive information, companies implement strict security measures to prevent data breaches. Analysts must follow best practices, such as using VPNs, encrypted storage, and secure access protocols, to protect company data.

Staying motivated in a remote environment can also be challenging. Without the structure of an office setting, it is easy to experience burnout or lose focus. Setting personal milestones, taking regular breaks, and engaging in team-building activities can help maintain motivation and a sense of connection with colleagues.

Conclusion

Succeeding as a remote data analyst requires a combination of technical expertise, effective communication, and strong work habits. By mastering SQL, Python, data visualization, and cloud-based tools, analysts can perform their tasks efficiently from any location. Adopting best practices such as maintaining clear communication, staying organized, and continuously learning ensures long-term success in a remote role. Despite the challenges, remote data analytics offers immense opportunities for professionals seeking flexibility and career growth. With the right skills and mindset, data analysts can build a successful and fulfilling remote career.

[shoshanews]

Learner Technicians Mechanical x4 (Generation) – Koeberg NPS Listing Reference: Learner Technicians Mechanical Listing Status: Open Position Summary - Company: Eskom - Industry: Energy & Power Generation - Job Category: Mechanical Engineering - Location: Western Cape, South Africa - Contract Type: Fixed-Term - Remuneration: Market-Related - EE Position: Yes - Closing Date: 17 March 2025 Introduction Eskom, a leading electricity provider in South Africa, is inviting applications for the Learner Technicians Mechanical x4 (Generation) at Koeberg Nuclear Power Station (NPS). This exciting opportunity is ideal for ambitious and self-motivated individuals who wish to develop their careers in the mechanical engineering field within the energy sector. Successful candidates will gain invaluable hands-on experience, technical training, and exposure to one of the most sophisticated nuclear power stations in the country. This learnership program is designed to equip learners with the necessary technical skills and knowledge required to work in Eskom’s Generation Division. It provides an opportunity to develop a strong foundation in mechanical engineering principles, workplace procedures, and technical problem-solving. Job Description The Learner Technicians Mechanical program is structured to offer practical on-the-job training while exposing candidates to Eskom’s operational environment. Candidates will undergo a structured development program where they will be trained in various aspects of mechanical engineering, power generation, and maintenance. Key responsibilities include: - Assisting in mechanical maintenance tasks under supervision - Participating in technical projects and on-site engineering activities - Learning and applying Eskom’s operational policies and procedures - Conducting safety inspections and ensuring compliance with engineering standards - Engaging in technical problem-solving and troubleshooting issues in power generation - Collaborating with various departments to gain practical exposure in different aspects of mechanical engineering - Completing technical reports and documentation related to maintenance and repairs This program provides candidates with structured mentorship, technical coaching, and industry exposure, preparing them for future career opportunities in the mechanical engineering sector. Ideal Candidate To be considered for the Learner Technicians Mechanical x4 (Generation) Program, candidates must meet the following minimum requirements: - Fully completed S4/S5/National Diploma/B Tech in Mechanical Engineering - Must be a South African citizen - Must be willing to undergo recruitment assessments as part of the selection process - Must demonstrate an interest in the energy and power generation industry - Ability to work in a highly regulated environment such as a nuclear power station - Must be willing to learn and adapt to Eskom’s policies, standards, and safety protocols Role Responsibility As a Learner Technician in Mechanical Engineering, the selected candidates will be responsible for: - Supporting Eskom’s Generation Division with mechanical-related tasks - Participating in scheduled plant maintenance activities to ensure optimal performance - Assisting senior technicians in fault-finding, diagnosing, and repairing mechanical systems - Learning how to operate specialized machinery and tools used in mechanical maintenance - Complying with safety regulations and industry-specific operational procedures - Attending technical training workshops and completing relevant coursework - Developing technical problem-solving skills and applying mechanical principles in a real-world setting - Gaining exposure to various power generation processes at Koeberg NPS Skills & Attributes Candidates applying for this learnership opportunity should possess the following skills and attributes: Leadership - Strong team player - Ability to work collaboratively with diverse teams - Eagerness to take initiative and lead small projects Behavioral Attributes - Integrity ��� Demonstrates honesty and ethical behavior - Professionalism – Maintains a high standard of conduct and accountability - Customer Focused – Committed to meeting customer and operational needs Knowledge - Understanding of Eskom’s policies and procedures - Familiarity with power generation processes and mechanical systems - Knowledge of technical standards within the mechanical engineering sector Technical Skills - Strong communication skills – Ability to report and document technical findings - Interpersonal skills – Works effectively with team members and supervisors - Negotiation skills – Ability to engage effectively with various stakeholders - Liaising skills – Ability to coordinate between different departments Personal Attributes - Politeness – Maintains a respectful and professional attitude - Promptness – Delivers assigned tasks within set deadlines - Energetic – Enthusiastic about learning and applying new skills - Self-starter – Able to work independently with minimal supervision - Assertive – Able to communicate effectively and take proactive measures Why Apply for Eskom’s Learner Technicians Mechanical Program? This Eskom learnership opportunity at Koeberg Nuclear Power Station offers several advantages for young professionals looking to launch their careers in the mechanical engineering sector: - Hands-on learning experience in a real-world power generation environment - Mentorship and technical guidance from industry professionals - Structured career development plan with exposure to high-tech mechanical systems - Opportunities to work on innovative engineering projects - Potential career growth within Eskom’s operations after successful completion of the program - Competitive remuneration and industry-recognized training How to Apply? If you meet the above minimum requirements and are passionate about starting your career in the energy sector, submit your online application through Eskom’s official career portal before the closing date on 17 March 2025. Ensure that your application includes: - An updated CV with relevant qualifications - Certified copies of your academic transcripts and ID - A motivation letter explaining why you are suitable for the position The Eskom Learner Technicians Mechanical Program is an excellent opportunity for engineering graduates looking to gain practical experience in power generation and mechanical maintenance. If you are eager to develop your technical expertise, work in a dynamic environment, and contribute to South Africa’s energy sector, this program is perfect for you. Apply today and take the first step towards an exciting career at Koeberg Nuclear Power Station! Click here to apply Read the full article

[global-research-report]

Data Center Accelerator Market Analysis: Meeting the Demand for Real-Time Data Processing

The global data center accelerator market size is anticipated to reach USD 63.22 billion by 2030, according to a new report by Grand View Research, Inc. The market is expected to grow at a CAGR of 24.7% from 2025 to 2030. The demand for data center accelerators is likely to grow owing to increasing adoption of technologies such as AI, IoT, & big data analytics. The COVID-19 pandemic had a positive impact on the data center accelerator market. Factors such as increased corporate awareness of the advantages that cloud services can offer, increased board pressure to provide more secure & robust IT environments, as well as the establishment of local data centers contributed to the growth of data center accelerators. Demand for businesses that rely on digital infrastructure has increased, which has led to significant growth in demand for data center network services in many industries. Data centers are now maintaining program availability and data security as more businesses and educational institutions already moved online.

Top industries using HPC are healthcare, manufacturing aerospace, urban planning, and finance. The University of Texas at Austin researchers are advancing the science of cancer treatment through the use of HPC. In a ground-breaking 2017 project, researchers examined petabytes of data to look for connections between the genomes of cancer patients and the characteristics of their tumors. This paved the way for the university to apply HPC in additional cancer research, which has now expanded to include efforts to diagnose and treat cases of prostate, blood-related, liver, and skin cancers.

Data Center Accelerator Market Report Highlights

Based on processor, the GPU segment accounted for the maximum revenue share of 44% in 2024. This can be attributed to the increasing use of GPU acceleration in IoT computing, bitcoin mining, AI and machine learning, etc. Moreover, GPU acceleration’s parallel processing architecture is useful in life science analytics such as a genome sequencing.

Based on type, the HPC data center segment is expected to grow at the highest CAGR of 26.0% over the forecast period. This can be attributed to a rising preference for hybrid and cloud-based high performance computing (HPC) solutions, use of HPC in vaccine development, advances in virtualization, etc.

Based on application, the deep learning training segment dominated the market in 2024. This can be attributed to increasing adoption of deep learning in hybrid model integration, self-supervised learning, high performance natural language process (NLP) models, and neuroscience based deep learning.

North America held the largest share of 37.0% in 2024 and is expected to retain its position over the forecast period. Presence of several data center accelerator solution and service providers makes North America a promising region for the market.

Asia Pacific is anticipated to expand at the highest CAGR of over 27.8% over the forecast period. Suitable government policies and the need for data center infrastructure upgradation in Asia Pacific are driving the growth of the data center accelerator market in the region.

In October 2020 Intel Corporation launched Intel Xeon Scalable Platform to assist secure sensitive workloads. This platform has new features that include Intel Platform Firmware Resilience (Intel PFR), Intel Total Memory Encryption (Intel TME), and new cryptographic accelerators to support the platform and advance the overall integrity and confidentiality of data.

Data Center Accelerator Market Segmentation

Grand View Research has segmented the global data center accelerator market report based on processor, type, application, and region:

Data Center Accelerator Processor Outlook (Revenue, USD Billion, 2018 - 2030)

GPU

CPU

FPGA

ASIC

Data Center Accelerator Type Outlook (Revenue, USD Billion, 2018 - 2030)

HPC Data Center

Cloud Data Center

Data Center Accelerator Application Outlook (Revenue, USD Billion, 2018 - 2030)

Deep Learning Training

Public Cloud Interface

Enterprise Interface

Data Center Accelerator Regional Outlook (Revenue, USD Billion, 2018 - 2030)

North America

US

Canada

Mexico

Europe

UK

Germany

France

Asia Pacific

China

India

Japan

Australia

South Korea

Latin America

Brazil

Middle East & Africa (MEA)

UAE

Saudi Arabia

South Africa

List of Key Players

Advanced Micro Devices, Inc.

Dell Inc.

IBM Corporation

Intel Corporation

Lattice Semiconductor

Lenovo Ltd.

Marvell Technology Inc.

Microchip Technology Inc.

Micron Technology, Inc.

NEC Corporation

NVIDIA Corporation

Qualcomm Incorporated

Synopsys Inc.

Order a free sample PDF of the Data Center Accelerator Market Intelligence Study, published by Grand View Research.

[alphabetsoup-blogposts]

Mixed feelings about that...

On the one hand, I know that the history of the world is, in part, a history of interesting, fairly bright (tho' I say so myself), mildly tortured individuals doing perfectly innocent, interesting, fairly bright things and triggering damaging and heavy-handed law enforcement scrutiny, not to mention social rejection. Literally, that's how it goes. I'm not going to list the times it's happened to famous historical figures because you will think I am comparing myself, when I'm not. I'm really just saying that divergent (if you like) types doing their thing often garner destructive suspicion and that seems—despite progress in recognising individual rights—to be something that society has not learned to avoid.

There are probably three reasons why this happens:

Said law enforcement personnel (and, indeed, ordinary members of society) say to themselves "Would I stay up night after night, for months on end, trying to come up with a reason why a stock market glitch dumped an unusually sequential series of prices on the public in July and pursuing said enquiry into wild historical and geopolitical rabbit holes? No. I. definitely. would. not. Ipso facto, this person must have a gainful motive and it must be suspicious. And, gosh, if I squint quite a bit and wiggle my nose, this looks like pre-cursor behaviour." I'm sympathetic (no, wait) because the "would I...?" test is a safety mechanism by which all of us judge the world and other human beings all. the. time. Here's mine: "Would I let children go to the park without adult supervision under 10 years old after twilight? No. I. would. not." But other parents do and they're not necessarily wrong, eh? The trick is hitting on the appropriate level of reaction and it's hard. I know that. Here's another one: public transport authorities ask us to report any unattended bags but we all know that 90% of them are just, well, unattended. The reporting system works, maybe, but only because the authorities don't immediately blow up people's belongings without first putting out a PA.

2. Lack of experience. I've been there too. When I was younger, I thought that every line of draft legislation was a toxic bomb waiting to go off and it was my job to find the flaw and explain how it could blow up for all concerned. I'd been trained to do that and I was super-keen to deploy my training. It's exciting to be at the center of the drama and when you're young or new or whatever, it causes you to lose the perspective that, actually, 99% of everything is just going to be perfectly normal and status quo-y. Truly market-destroying legislative provisions don't come along all that often (any more) and nor do middle-aged, British, Christian, single mum, PhD ISIS-sympathisers (or whatever they thought I was).

3. If your natural tendencies are towards the pedestrian and the unimaginative, you are just unable to grasp the impact of your "subtle" surveillance techniques on interesting, fairly bright (tho' I say so myself), mildly tortured individuals. I think that's self-explanatory. In short, we all process verbal and non-verbal cues from other people all of the time but some of us who are over-sensitised find the emotional data that comes from the verbal cues coupled with the non-verbal cues overwhelming while others don't. It's hard for the latter, I think, to know what life is like for the former and to imagine the ripples that will flow from throwing a pebble into the waters.

So there is plenty that I (if not you) am happy to forgive, believe it or not. Including any warranted searches of my house or possessions and formal checks on my phone records and internet browsing history or whatever. I would obviously greatly prefer my stuff to be private—not least because I think the information has fallen into the wrong hands—but, in principle, I am okay with being checked out in a formal and procedural way. What I will never forgive is the informal snooping and surveillance at work—and it's unclear to me that there would have been any "warranted" searches without that—and the feedback seeding of my life with death talk and such like. And, indeed, when I say "never forgive", I don't think you have quite apprehended even now, how serious I am about that and how complete a bar it is to anything that resembles the Establishment's "Project 25".

When someone gave K—a person I distrusted and resented from mid-2017—a piece of confidential information in May 2018 about my son's timetable ("Ian Bostridge")* that I didn't yet know...well, that was the equivalent of going nuclear from the off ...of blowing up someone's luggage without first asking "does anyone claim this bag" (only so, so much worse). It allowed her to deliver a verbal ticking bomb which would only detonate when I got home later that day and found out that my son had plans to see Ian Bostridge,** while she rambled on for nearly an hour about "targets"—and, oh, just so much more. This, after my son had already been "kidnapped" (well what would you call it?) aged 9 and driven to the Tower of London in the dark by "a man with a Russian or German accent, Mum" only to be dropped off away from my house, shivering bitterly in his PE kit in January.... you get the gist. TLDR? Whoever released that information made an enemy for life. No ifs, no buts. #ttd.

*I made his father cancel the tickets. Just, fyi, his part in this was perfectly normal... I would ordinarily expect him to take my son to a classical music event at that venue. It is a thing that he does.

** It is absolutely impossible that K was simply asking about "Ian Bostridge" casually for 00s of reasons. There is no point at which I have revisited that conversation and thought "well, perhaps that was just innocent small talk". If you want the most "innocent"—ie, least malevolent—explanation, it is probably that someone was seeding a whole group of my contacts with anagrams to push, eg, "Ian Bostridge is an anagram of: Big Reds to Ian [Fleming Airport, Jamaica]" and, by tragic coincidence, my son's father decided to buy tickets to a concert while K decided to go all "the Mariner hath his will" on it. A less likely explanation is that someone decided to seed such a group with perfectly ordinary codes thus: "it would be useful to get Joanna to contemplate the subtextual nature of the word 'singer'" and then, by some extraordinary coincidence, two of those contacts hit on "Ian Bostridge" as a useful way to introduce the term etc etc.

[williammason1]

William Mason: How Investors Rely on Regulatory Bodies to Prevent Deception

In the financial market, investors face not only the risk of market fluctuations but also the threat of various forms of financial scams. As a financial expert, William Mason believes that regulatory authorities play a pivotal role in protecting investors from financial scams. This article delves into how regulatory bodies employ multiple measures to help investors identify and prevent scams, ensuring market fairness and transparency.

Firstly, regulatory authorities establish and enforce financial regulations to standardize market behavior and safeguard the legal rights of investors. These regulations encompass not only the standardization of financial products and services but also the operational norms for financial institutions. William Mason points out that the complexity and diversity of the financial market often make it difficult for investors to assess the risks of various financial products. By setting stringent regulations and oversight standards, regulatory bodies can prevent malicious actors from exploiting complex financial instruments for scams, thereby reducing the likelihood of investor deception.

Secondly, regulatory authorities play a significant role in the supervision and review of the financial market. Through rigorous scrutiny and oversight of the daily operations of financial institutions, regulatory bodies can promptly detect and curb potential violations. For instance, regulators examine the financial health, fund flows, and market activities of financial companies to ensure operational transparency and legality. William Mason believes that this supervisory mechanism not only helps prevent financial scams but also boosts investor confidence in the market, encouraging more rational investment decisions.

Moreover, regulatory authorities assist investors in obtaining accurate and timely market information through disclosure systems. In the financial market, transparency of information is a key factor in preventing scams. By mandating that financial institutions and listed companies regularly disclose their financial status, operating performance, and significant events, regulatory bodies ensure that investors can make informed decisions based on comprehensive information. William Mason notes that strict enforcement of disclosure requirements helps reduce information asymmetry in the market, preventing some malicious actors from using insider information or false data to deceive investors.

Regulatory authorities also encourage the public and market participants to report suspicious activities through established whistleblowing mechanisms. By providing dedicated reporting channels and protecting whistleblowers, regulatory bodies can quickly obtain leads on potential illegal activities in the market and take swift action. William Mason believes that such reporting mechanisms enhance the self-regulatory capacity of the financial market and increase public trust in market order, further preventing financial scams.

Lastly, regulatory authorities enhance public financial literacy and scam awareness through financial education and investor protection programs. By regularly issuing market risk alerts, organizing investor education events, and offering online learning resources, regulatory bodies help investors understand the workings of the financial market and common scam tactics. William Mason asserts that investor awareness and knowledge of finance are the first line of defense against scams. Through educational initiatives and guidance from regulatory bodies, investors can better identify and guard against potential scams, thereby securing their assets.

In summary, the role of regulatory authorities in preventing financial scams is indispensable. Through the establishment and enforcement of regulations, enhanced market supervision, promotion of information disclosure, implementation of whistleblowing mechanisms, and improvement of public financial literacy, regulatory bodies provide robust protection for investors against scams. William Mason hopes that investors will fully utilize the resources and support offered by regulatory authorities, strengthen their awareness of scams, and make more informed investment decisions in the complex and volatile financial market, ensuring the safety of their investments.

[industrynewsupdates]

Laundry Services Procurement Intelligence: A Comprehensive Guide

The global laundry services category is anticipated to grow at a CAGR of 7.0% from 2023 to 2030. Growth of the category can be attributed to rising demand from the hospitality & healthcare sector, consumer prioritization for well-maintained and clean garments, rapid urbanization, rise in disposable income, and emergence of online and on-demand laundry services. Moreover, the category is witnessing an increase in end-usage among restaurants, educational establishments such as schools and colleges, and salons. For instance, in hotels and hospitals, it is crucial to maintain immaculate uniforms and linens, due to stringent hygiene and quality standards. 

Outsourcing laundry services provides several benefits to end-users such as cost savings, time efficiency, and compliance to safety regulations (e.g., using authorized cleaning agents). Few of the key challenges in this category include equipment management (e.g., replacing ageing equipment and maintaining new equipment), rising operational costs, meeting customer preferences that vary according to end-use, staff shortages, and technology integration. For instance, in Q4 2023, the laundry cost index increased by 9.3% due to a rise in global energy prices. Moreover, in 2023, regional laundry service providers in Australia and New Zealand faced labor shortages due to a rise in labor costs. In another instance, in 2021, certain key laundry service providers in the UK struggled to meet demand from hotels and National Health Service (NHS) facilities due to staff shortages.

Key technological advancements driving the global laundry services category include Artificial Intelligence (AI) and Machine Learning (ML), use of smart and digital laundry equipment, waterless laundry, Internet of Things (IoT)-enabled cleaning appliances, and software-driven management systems. AI and ML use algorithms to assess data from laundry equipment which is then used to optimize laundry processes with respect to time and efficiency. ML can help in predicting maintenance issues in laundry equipment and evaluate laundry preferences of customers. Smart and digital laundry equipment such as smart washing machines are endowed with self-cleaning programs and can be operated via smartphones. Moreover, they also have features such as automatic detergent dispensers and smart diagnostic tools. Additionally, features such as Radio Frequency Identifications (RFID) help smart machines to determine the type of wash required. IoT enabled cleaning appliances are equipped with ‘Wi-Fi’ and ‘Bluetooth’ options to facilitate the monitoring of incident detection, machine status, wash cycles, and remote supervision which makes it easier for service providers to enhance operational efficiency. 

Order your copy of the Laundry Services Procurement Intelligence Report, 2023 - 2030, published by Grand View Research, to get more details regarding day one, quick wins, portfolio analysis, key negotiation strategies of key suppliers, and low-cost/best-cost sourcing analysis

Software-driven management systems are equipped with cloud-based technologies and can provide real-time feedback related to operational efficiency and service performance. Waterless laundry can reduce the quantity of water being consumed by 90%, thus making it cost-effective and environmentally friendly.

The laundry services category is fragmented and consists of a large number of global market players, turning the category to be competitive. Key players in the category set themselves apart by continuously upgrading equipment with latest technologies, improving turnaround time, optimizing service quality, engaging in strategic partnerships, adopting effective marketing strategies, having a strong digital presence, and emphasizing customer satisfaction in order to enhance their service portfolio and to stay competitive. Moreover, key players are actively focusing on improving environmental sustainability by using energy-efficient equipment and eco-friendly detergents, and ensuring frugality in water usage. Additionally, key players are also focusing on improving the overall customer experience by offering tailored pricing plans, contactless pickup and delivery, on-demand and express services, and catering to personalized packaging preferences. Buyers in the category possess high bargaining capability owing to an extensive supply base.

Labor, equipment, detergents and chemicals, maintenance and repair, energy, and other costs such as rent and utilities, transportation and logistics, sales and marketing, compliance, insurance, and taxes are the key components of this category. Labor and equipment account for the largest share of the cost structure. A prominent pricing structure used in this category is unit pricing or per-piece pricing, in which rates are charged based on the number of items being laundered. Another key pricing structure is weight-based pricing, wherein the prices are determined by the weight of the laundry load. Periodic pricing or subscription-based pricing is also used, wherein customers pay a pre-determined fee on a weekly or monthly basis in exchange for services. Few key service providers have a tiered pricing that varies by volume, frequency, and type of item. Few of the key factors affecting the prices are fluctuations in labor costs, rise in industrial electricity prices, and high cost of equipment replacement and upgradation. Additionally, the pricing may vary based on the length of contracts.Buyers and service providers prefer longer-term contracts for added security and stability, steady pricing structure, and stronger partnerships. According to data published by FRED, the Producer Price Index (PPI) for commercial laundry and dry-cleaning machinery and equipment in the U.S. increased from 333 in December 2022 to 348 in May 2023, which contributed to a rise in the total costs of commercial laundry services in the U.S. during this period.

Asia Pacific dominates the global laundry services category, holding a significant portion of the global market share. Key driving factors for this region include rapid urbanization, improved demand from emerging economies such as India and China, and rapid growth among leading end-user segments such as hospitality and healthcare. Few of the leading players such as Alliance Laundry Systems LLC have been focusing on capacity expansions in Asia Pacific to cater to the high demand. Key driving factors in developed regions such as North America and Europe include high degree of urbanization, emphasis on time-saving solutions, technological advancements, and stringent hygiene guidelines in facilities such as hotels and hospitals. Asia Pacific is expected to continue its dominance during the forecasted period due to a surge in the number of facilities such as hotels, hospitals, restaurants, salons, schools, and colleges that are outsourcing commercial laundry services. Comparing the prices charged by various service providers, assessing service capabilities based on pickup and delivery options, lead time, and minimum order volume, evaluating the experience level of service providers, comparing technologies used in equipment and service provision, measuring service quality based on customer testimonials, and checking adherence to safety and environmental norms are some of the best sourcing practices considered in this category.

Browse through Grand View Research’s collection of procurement intelligence studies:

• Sodium Cyanide Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

• Carbon Steel Procurement Intelligence Report, 2023 - 2030 (Revenue Forecast, Supplier Ranking & Matrix, Emerging Technologies, Pricing Models, Cost Structure, Engagement & Operating Model, Competitive Landscape)

Laundry Services Procurement Intelligence Report Scope

• Laundry Services Category Growth Rate: CAGR of 7.0% from 2023 to 2030

• Pricing Growth Outlook: 5% - 10% increase (Annually)

• Pricing Models: Unit pricing, Weight-based pricing, Subscription-based pricing, and Tiered pricing

• Supplier Selection Scope: Cost and pricing, Past engagements, Productivity, Geographical presence

• Supplier Selection Criteria: Industries served, years in service, revenue generated, geographic service provision, employee strength, certifications, type of laundry service, technological capabilities, minimum order volume, pickup and delivery options, lead time, and others

• Report Coverage: Revenue forecast, supplier ranking, supplier matrix, emerging technology, pricing models, cost structure, competitive landscape, growth factors, trends, engagement, and operating model

Key Companies 

• Alliance Laundry Systems LLC

• Alsco, Inc.

• Aramark Corporation

• Cintas Corporation

• Lapels Dry Cleaning

• Laundryheap Limited

• Marberry Cleaners & Launderers, Inc.

• PRESSTO ENTERPRISES, S.L.U.

• Rinse, Inc.

• The Huntington Company

• Tide Cleaners

• UniFirst Corporation

Brief about Pipeline by Grand View Research:

A smart and effective supply chain is essential for growth in any organization. Pipeline division at Grand View Research provides detailed insights on every aspect of supply chain, which helps in efficient procurement decisions.

Our services include (not limited to):

• Market Intelligence involving – market size and forecast, growth factors, and driving trends

• Price and Cost Intelligence – pricing models adopted for the category, total cost of ownerships

• Supplier Intelligence – rich insight on supplier landscape, and identifies suppliers who are dominating, emerging, lounging, and specializing

• Sourcing / Procurement Intelligence – best practices followed in the industry, identifying standard KPIs and SLAs, peer analysis, negotiation strategies to be utilized with the suppliers, and best suited countries for sourcing to minimize supply chain disruptions

[blogchaindeveloper]

The Rise of AI Agents

In the ever-evolving landscape of technology, artificial intelligence is no longer a futuristic concept—it’s a present-day force reshaping how professionals work, communicate, and innovate. One of the most transformative developments in this field is the rise of AI agents—intelligent systems designed to operate autonomously, collaborate with humans, and complete complex tasks across industries. These agents are becoming indispensable tools for professionals, offering efficiency, accuracy, and innovation at scale.

For those looking to leverage this emerging technology in their careers, educational credentials such as the Certified Agentic AI Expert™, AI Course, Gen AI Course, ChatGPT Course, and Blockchain Certification are paving the way for deep understanding and practical application.

What Are AI Agents?

AI agents are software programs equipped with the ability to perceive their environment, interpret goals, plan actions, execute tasks, and learn from outcomes—all with minimal human supervision. Unlike traditional AI systems that rely on specific commands or narrow tasks, AI agents can operate in dynamic environments, solve problems proactively, and make decisions in real time.

Whether it's managing emails, summarizing documents, scheduling meetings, analyzing financial reports, or writing code, AI agents can serve as digital assistants that not only perform routine tasks but also adapt and improve over time.

Why Professionals Are Turning to AI Agents

Professionals across industries—whether in finance, marketing, law, healthcare, or tech—are increasingly embracing AI agents for several reasons:

Time-Saving Automation: AI agents handle repetitive and administrative tasks, freeing up time for strategic thinking.

Data-Driven Decision Making: Agents can analyze massive datasets, extract insights, and present actionable recommendations in seconds.

Scalability: Unlike human teams that scale with headcount, AI agents scale with code—enabling one individual to do the work of many.

24/7 Availability: AI agents don’t sleep, take breaks, or need vacation—making them ideal for global businesses that operate across time zones.

Core Capabilities of AI Agents

Natural Language Understanding: Many agents are powered by large language models (LLMs), like OpenAI’s GPT or Google’s Gemini, allowing them to understand and generate human language fluently. This makes them ideal for tasks like drafting emails, responding to queries, and summarizing long-form content.

Multi-Step Reasoning: Unlike basic chatbots, modern AI agents can reason through multi-step problems. For example, a legal assistant agent could review a contract, identify risk clauses, cross-reference regulatory guidelines, and draft revisions.

Tool Integration: AI agents can be programmed to use tools like web browsers, spreadsheets, APIs, and databases. This allows them to go beyond static responses and perform actions—booking appointments, sending reports, or pulling data from external systems.

Memory and Personalization: Some agents are equipped with memory modules that allow them to remember user preferences, prior interactions, and contextual details. This enables more personalized and efficient workflows over time.

Self-Improvement: Through feedback and training loops, AI agents can refine their behavior, improve accuracy, and adapt to changing environments—similar to how humans learn from experience.

Real-World Applications by Role

Marketers use AI agents to generate social media content, analyze campaign performance, and automate customer segmentation.

Lawyers deploy agents to review case files, extract legal precedents, and draft initial versions of legal documents.

Doctors and medical researchers benefit from AI agents that summarize medical journals, flag anomalies in patient records, or suggest treatment options.

Financial analysts rely on AI agents to monitor markets, forecast trends, and create dynamic reports for clients.

Software developers can delegate bug tracking, documentation, and even code writing to intelligent agents.

Building and Managing AI Agents: Training & Credentials

To work effectively with AI agents—or build your own—it’s essential to acquire the right training. Here are some key credentials that provide the necessary skills:

Certified Agentic AI Expert™: This certification, ideal for business leaders, strategists, and consultants, focuses on understanding agentic systems, ethical frameworks, AI governance, and implementation strategies across sectors.

Certified Agentic AI Developer™: This program, geared toward developers and technical professionals, offers hands-on training in building autonomous AI systems. It includes working with Python, LLMs, APIs, and frameworks like LangChain to develop production-ready agents.

AI Course (Fundamentals to Advanced): A general-purpose course for beginners or professionals, covering everything from machine learning basics to advanced neural networks and deployment strategies.

Gen AI Course (Generative AI): Specializes in using AI to create content, images, text, and code. Professionals in the creative, marketing, and media fields benefit enormously from these skills.

ChatGPT Course: Focused on prompt engineering, fine-tuning, and deploying GPT-based systems for customer support, knowledge management, and task automation.

Blockchain Certification: As AI agents increasingly interact with decentralized platforms, a blockchain certification helps professionals understand how to integrate agents with smart contracts, decentralized identity systems, and secure data layers.

Challenges and Considerations

While AI agents offer substantial benefits, they also come with challenges:

Ethical Use: It’s vital to ensure that AI agents act within legal and ethical boundaries—especially in sensitive industries like healthcare or finance.

Security: Since agents often access sensitive data, robust cybersecurity and access controls are a must.

Bias and Fairness: Developers must be vigilant about bias in training data and ensure fairness in decision-making processes.

Oversight: Professionals should treat AI agents as collaborators, not replacements. Human oversight is crucial for quality control and strategic alignment.

Final Thoughts

AI agents are transforming the professional world—not by replacing humans, but by augmenting their capabilities. As organizations look for faster, smarter, and more adaptive ways to operate, the demand for intelligent agents—and those who can build and manage them—is surging.

Whether you're a beginner exploring an AI course, enhancing your creative edge through a Gen AI course, diving deep with a ChatGPT course, or specializing through a Certified Agentic AI Expert™, Certified Agentic AI Developer™, or Blockchain Certification, there’s never been a better time to integrate AI agents into your professional journey.

The workplace of the future will be built not just by humans, but by teams of humans and AI agents working side by side. And the professionals who master this collaboration will lead the way.

[remote-workers]

Essential Qualities for Remote Workers: Sought-After Traits

As the world continues to embrace remote work, the job market has witnessed a significant transformation. The demand for remote workers has skyrocketed, with 77% of remote employees reporting increased productivity in their off-site work environments. To thrive in this burgeoning work-from-home landscape, it's crucial to understand the qualities employers seek in remote workers and prepare effectively for remote work interviews. In this article, we'll explore these essential attributes and provide tips to help you become the ideal remote worker.

Key Takeaways:

Remote workers must excel in strong communication skills, technical proficiency, self-motivation, initiative and confidence, and excellent time management. Prior remote work experience is a valuable asset, showcasing your ability to succeed independently in a virtual setting. Preparing for remote work interviews involves researching the company, understanding the remote work environment, highlighting relevant experience, showcasing technical proficiency, and being ready for video interviews. Essential Qualities for Remote Workers

Strong Communication Skills: Effective communication is the cornerstone of remote work. With face-to-face interactions replaced by technology-mediated communication, the ability to convey information clearly and efficiently becomes critical. It includes proficiency in written communication, agility in video calls, and effective use of instant messaging platforms. Strong communicators are adaptable and integrate seamlessly into virtual teams.

Technical Proficiency: In the digital age, remote workers rely heavily on online platforms and software tools. Technical proficiency is no longer optional; it's essential. This extends beyond basic computer skills to troubleshooting common tech issues and mastering job-specific programs and apps. Technical expertise can be the difference between project success and failure in remote work.

Self-Motivation: Self-motivation is the driving force behind successful remote work. In the absence of constant supervision, self-motivated individuals set and achieve objectives, prioritize tasks, and maintain personal accountability. They exhibit resilience and adaptability, making them invaluable assets in remote teams. Self-motivation trumps technical proficiency since computer skills can be learned, but inner drive comes from within.

Initiative and Confidence: In remote work, there are no physical supervisors or coworkers to provide guidance or reassurance. Remote workers must take the initiative to seek information, find solutions, and manage their workload. Confidence in making independent decisions and succeeding without constant supervision is crucial.

Excellent Time Management: Remote employees have the freedom to set their own schedules and work at their own pace. Effective time management is essential for meeting deadlines and staying focused on tasks. Employers value individuals who can prioritize their workload, create productive schedules, and consistently deliver high-quality work on time.

Prior Remote Experience

Having prior remote work experience is a significant asset when seeking remote positions. It demonstrates your ability to work independently, stay focused, meet deadlines, and solve remote work-related challenges. It also highlights your self-motivation and confidence in your abilities to work without direct supervision. Employers appreciate candidates familiar with the tools and technologies commonly used in remote work.

How to Prepare for Remote Work Interviews

To increase your chances of securing a remote job, follow these essential tips when preparing for remote work interviews:

Research the Company: Thoroughly research the company you're interviewing with. Familiarize yourself with their mission, values, and recent news or projects. This demonstrates your commitment to the role.

Understand the Remote Work Environment: Be aware of the unique challenges and opportunities of remote work. Be ready to discuss how you stay motivated, manage your time effectively, and communicate in a virtual workspace.

Highlight Relevant Experience: Showcase any previous experience working independently or from home. Discuss situations where you demonstrated self-motivation, initiative, and effective communication skills.

Showcase Technical Proficiency: Emphasize your technical skills during the interview. Comfortably use virtual meeting platforms, project management tools, and other relevant software.

Be Ready for Video Interviews: Virtual interviews are common for remote positions. Familiarize yourself with video conferencing platforms and test your audio and video settings.

Practice Common Remote Job Interview Questions: Prepare for common remote job interview questions. Rehearse responses that demonstrate your ability to work independently, collaborate virtually, and maintain strong communication.

Create an Optimal Home Office Setup: Mention any dedicated workspace or equipment that allows you to work efficiently from home. Highlight your organization skills and ability to create a productive environment.

Conclusion

In conclusion, employers seek remote workers who possess specific essential qualities, including strong communication skills, technical proficiency, self-motivation, initiative and confidence, and excellent time management. Prior remote work experience and effective preparation for remote work interviews can significantly enhance your chances of securing remote job opportunities. By showcasing these sought-after qualities and thoroughly preparing, you can position yourself as a valuable asset in the growing world of remote work. Mastering the art of remote work is not just a skill; it's a game-changer in today's dynamic job market.

[metamoonshots]

Sui Community – a layer 1 blockchain – has gained important traction since its mainnet launch in Might. Nonetheless, South Korean regulators consider the builders lied about a number of elements of the token. In keeping with the most recent report by an area information company, the director of the Monetary Supervisory Service (FSC) stated that an investigation might be carried out to find out whether or not SUI is working as a fraudulent scheme. Whereas the principle bone of competition is SUI’s freefalling value because the token misplaced over 91% of its worth, the Sui Basis, alternatively, has denied the accusations. South Korean Authorities’ Accusations Throughout the Governme­nt Affairs Committee audit, the South Korean regulator claimed that this drop might be attributed to their “false” claims relating to the circulating provide, which the workforce behind SUI has allegedly failed to handle. Democratic Celebration lawmaker Min Byung-deok’s statement relating to the matter learn, “The value of Sui Coin has plummeted, and the principle cause is that they lied concerning the quantity in circulation, however they don't seem to be elevating the problem. It has fallen greater than 67% within the 5 months since itemizing. The issuer, Sui Basis, acquired self-interest by staking (depositing) the locked-up quantity and bought it to extend circulation.” The regulator additional blamed the issuer, the Sui Basis, and accused it of prioritizing private achieve by unblocking a portion of the provision and promoting it to inflate the circulating quantity.” Moreover, Digital Asset Alternate Alliance (DAXA), a consortium comprising main cryptocurrency exchanges in South Korea, confronted criticism for purportedly neglecting to confirm SUI’s circulating supply. The consultant argued that no actions had been taken towards SUI, though it clearly violated the rules established by the alliance chargeable for overseeing the cryptocurrency business within the nation. In response, FSC Director Lee Bok-hyun urged DAXA to implement adequate measures to rebuild client belief. He emphasised that if any manipulation of distribution quantity happens by staking or unfair disclosure, they are going to provoke consultations and implement the suitable actions. Director Lee additionally highlighted the presence of institutional limitations, noting that the just lately enacted Digital Asset Person Safety Act lacks important provisions for supervising major markets and exchanges. He confused the need for additional dialogue within the subsequent legislative section. SUI Basis Responds The muse behind the event of the SUI ecosystem said that the statements made by the authorities had been “unfounded and materially inaccurate.” In a message posted on X (previously Twitter), the SUI Basis affirmed that it has not engaged in any liquidation of SUI tokens, together with these acquired as staking rewards. They emphasised that every one SUI token transfers are seen and verifiable on the blockchain whereas underscoring their “constant and clear” communication with the group relating to the SUI token’s circulating provide schedule. SPECIAL OFFER (Sponsored) Binance Free $100 (Unique): Use this link to register and obtain $100 free and 10% off charges on Binance Futures first month (terms).PrimeXBT Particular Supply: Use this link to register & enter CRYPTOPOTATO50 code to obtain as much as $7,000 in your deposits.

[market-research-reports-fmi]

The global self-supervised learning market is projected to have a moderate-paced CAGR of 33.4% over the forecast period. The current valuation of the self-supervised learning market is US$ 12.46 billion in 2023. The value of the self-supervised learning market is anticipated to reach a high of US$ 222.31 billion by the year 2033.

Self-reinforcement learning has emerged as a viable machine learning technique to address the challenges brought on by an overreliance on labelled data. For a very long time, creating intelligent systems using machine learning techniques has required the availability of high-quality tagged data. Because of this, it will be difficult to overcome the high cost of high-quality annotations during the training process.

[potteresque-ire]

More ask answer about Word of Honour (山河令, WoH) and the so-called “Dangai 101 phenomenon” under the cut ~ with all the M/M relationships shown on screen, does it mean improved acceptance / safety for the c-queer community?

Due to its length (sorry!), I’ve divided the answer into 3 parts: 1) Background 2) Excerpts from the op-eds 3) Thoughts This post is PART 2 💛. As usual, please consider the opinions expressed as your local friendly fandomer sharing what they’ve learned, and should, in no ways, be viewed as necessarily true. :)

(TW: homophobic, hateful speech quoted)

The following are three opinion pieces published by state-controlled media re: Dangai and WoH:

O1) Published on 2021/03/04, in Shanghai Observer 上觀新聞

8.6分爆款武俠劇《山河令》背后，是90后愛看的江湖 Behind the 8.6-score Wuxia drama WoH is the Jianghu loved by those born after 1990

[Pie note: the 8.6 score refers to the score WoH got from the popular TV and film review site, Douban]

O2) Published on 2021/03/16, in China Comment 半月談:

國產電視劇掀起「耽改」熱：「腐文化」出圈，青少年入坑 The Rise of Dangai in C-dramas: “Rot Culture” exits Circle, Youth fell into the Ditch

and its related editorial:

「耽改劇」 盛行？警惕對「腐文化」進行無底線炒作和過度消費 Dangai Dramas Prevailing? Be alert to the Uncurbed Hyping and Excessive Consumption of “Rot Culture”

[Pie Note: “Exiting the Circle” (出圈) and “Falling into the Ditch” (入坑) are both fandom vocabularies. “Exiting the circle” refers to something being so famous that it is no longer contained within fandom (the circle) and instead, breaks into public consciousness, mainstream. “Falling into a Ditch” means to fall for a fandom so hard that one cannot crawl their way out it. For example, c-turtles commonly refers to their joining the YiZhan fandoms as ditch falling, followed by being “hammered to the bottom of the ditch” by Gg and Dd’s candies.

“Rot” 腐 refers to the same rot as in fujoshi 腐女 and “rot selling” 賣腐 described in PART 1.]

O3) Published on 2021/04/07, in 光明日報 Enlightenment Daily

耽美作品改编盛行带偏大众审美 Popularity of Dangai Dramas leads the Public’s Aesthetic Astray

To summarise first,

* Article O1 was very light on the characterisation of Danmei—the terms Danmei and Dangai never even appeared in the article. It focused, instead, on WoH’s Wuxia elements, including the beauty of its presentation—much like People Daily’s review of TU focused on the drama’s aesthetics, including its world view. The relationship between Zhou Zishu and Wen Kexing was never mentioned, not even garnering a description such as 摯友 (“close friend”) as LWJ and WWX did. The article did point out that the drama was catering to a women audience.

* Article O2a (the opinion piece) and O2b (the editorial) are about Danmei and Dangai, collectively as the subculture they named “Rot Culture” (腐文化). No drama names are mentioned (in reading Chinese news, it’s important to note whether the critiqued target is named or not; the former (點名批評) is considered significantly harsher). The article, as hinted by the word “rot” in its title, leaned heavily towards characterising Danmei and Dangai by the traditional BL characterisation. Article O2a was also the only article out of the four that explicitly addressed  homosexuality. Rather than addressing the queer elements in Danmei/Dangai as queer, however, the article argued the genres could turn their young audience queer.

* Article O3 is also about Danmei and Dangai as the “Rot Culture” subculture, without the naming of any dramas. This article is notable for its association of the genres and the state’s concern with the “feminisation” of Chinese men.

Based on these op-eds, the state is characterising Danmei and Dangai predominantly as characterisation 2 — traditional BL, women’s fantasy. They recognised the psychological need behind the popularity of the genres among their (het) women audience, and the tone, is overall, of understanding and approval:

One of the cores of Dangai is the pursuit of “beauty”. The “double male leads” in Dangai dramas score sufficiently high beauty points to become the party to be defined, to be gazed, to be consumed. It is a counterattack to the male gaze. In addition, such “double male leads” enjoying equal relationship, admiring each other and fighting together shoulder-to-shoulder, also reflects the ideals of women towards relationships.

In the visual world of Dangai, two beautiful men respecting and treasuring each other, progressing together shoulder-to-shoulder, not only fits with women’s ideal model of  relationships, but also also create wide, yet-to-be filled emotional spaces for women’s unstoppable imagination to flex. Such relationships have less considerations of reality and self-interest, and thus appear to be more pure.

However, these opinion pieces have also made clear that the state saw the queer elements surrounding the genre, and its opinion of them is much more ��� reserved, especially when they cross the fiction / reality line and become the focus of the promotion of the dramas via the actors, who straddle that fiction / reality line.

Due to the lengths of these articles, I’m only translating the notable “chunks” in each of them—the “chunks” that connect the genres with queerness. I’m deliberately keeping these passages as “chunks”—ie, without removing sentences in the middle—to highlight the state’s logic in making the connection.

From O2a: 國產電視劇掀起「耽改」熱：「腐文化」出圈，青少年入坑 The Rise of Dangai in C-dramas: “Rot Culture” exits Circle, Youth fell into the Ditch

“M/M CP”, “Beautiful Men Economy”, topics surrounding this market—today, nobody bets an eye anymore at “selling the rot” being the industrial phenomenon. “Sell the rot” is to sell “rot culture”, with “rot culture” being the subculture for the audience’s imagination, of M/M (ambiguous) love stories for major content.

Such subculture, if confined within its fandoms, may be harmless. However, if it is to be adapted into TV dramas in significant scale, if it is to break through the subculture circles and enter the realm of general public entertainment, then one must take caution of its bad influence, especially to inexperienced youths.

With the established review system for web and TV dramas, production teams often remove the “romantic plot line” between the two male leads in the original Danmei canon and display “brotherhood love” in the TV drama, while “playing edge ball” to provide their audience with room for imagination. In the subsequent promotion and marketing, however, the two male actors may have to “sell the rot” as well.

[Pie note: I’m translating 打擦边球 literally as “playing edge ball” as this is a very commonly used term in discussions of China’s censorship. It means to step as close to the forbidden line as possible without crossing it, to take advantage of loopholes.]

Author of the article “On the Danmei-ization of Chinese Dramas” believes that, in recent years, CPs “selling the rot” , the practice of which is rooted in Danmei culture, have become a hit in the Chinese TV industry. TV dramas with Danmei elements entice their audience to create CPs around the leads of the dramas; they make use of the fervour generated by the discussion topic to achieve high viewership.

In recent years, academics have already expressed concern and investigated the influence of Danmei culture on the youth’s gender awareness, their opinions of marriage etc. For example, the article “Sexual Orientation of Some Youths in Hunan Province and Analysis of their Potential Causes” investigated the sexual orientation of 1,260 youths in the province and discovered that: among males, 2.9% self-identified as homosexuals, 4.9% bi-sexuals, 12.4% unknown; among females, 2.4%, 12.4%, 14.3% respectively. 37.5% of the people knew about Danmei or Doujin (同人; fandom), among which 32.3% indicated they “liked” it. 11.9% indicated that they longed for the homosexual romance in such works.

The author of the article analysed that, students who knew about Danmei or Doujin were more likely to report bisexuality or unknown sexual orientation. This demonstrated the influence of such culture on the sexual orientation of youths.

( Cartoon from O2a, titled “Learning to be “cool” 學酷 )

From O2b:「耽改劇」 盛行？警惕對「腐文化」進行無底線炒作和過度消 Dangai Dramas Prevailing? Be alert to the Uncurbed Hyping and Excessive Consumption of “Rot Culture”

Not to be overlooked is this: the severe reality of “Rot culture” exiting the circle and becoming immensely popular is urgently awaiting the entire society’s alert and attention. Objectively speaking, many Dangai works are not aspiring to positively, proactively guide and display Danmei culture, but only to set up attention-grabbing gimmicks, the purpose of which is solely to “sell the rot”. Not a small number of Dangai’s plots are illogical. Worse, in order to attract attention and satisfy the “taste” of fans, some production companies are forcibly selling “M/M CPs”,  conducting “bound” promotion [Pie note: as in bound by CP pairing] and embarrassing interactions [Pie note: as in, getting the actors to interact in a suggestively romantic way] , “playing the edge ball” [Pie note: as explained above] to generate personalities, consuming “Rot Culture” without a bottom line. These poor marketing tactics not only hurt the interest of Danmei audience, but interfere with the online environment and its order. The indulgence of radical language, moreover, challenges and affects mainstream values. These bad influences must be paid attention to and supervised.

From O3) 耽美作品改编盛行带偏大众审美 Popularity of Dangai Dramas leads the Public’s Aesthetic Astray

In addition to the explosion of the number of Dangai dramas, many dramas that are not originally Dangai are attaching themselves to the Dangai genre, by setting up double male leads, by playing up the suggestive atmosphere between male characters in their plot lay out. Some variety shows make use of the plot setup, the post-editing, the promotion of topics etc, to forcibly pair up their male guests for the purpose of hype and attention. This vulgar custom of “playing edge ball” as a means to tempt, to lead the audience into indulging in fantasies [Pie note: sexual fantasies implied by the idiom 想入非非] have spread from visual media production to the areas of promotion and marketing. Some interviews, magazine photoshots, short video production have also joined the bandwagon of borrowing the popularity of Danmei culture. They use all sorts of sensitive topics to tease and excite the public, tirelessly, happily guiding the fans to overanalyse Dangai dramas and even, the relationship between the actors of Dangai dramas. With the push of such gimmicks, Danmei is reaching the public through multiple channels, gathering popularity and turning into a phenomenon.

From O3) 耽美作品改编盛行带偏大众审美 Popularity of Dangai Dramas leads the Public’s Aesthetic Astray

Men with delicate looks, with traditionally feminine (soft and reserved) quality, are often sought after by the rot women (fujoshis). There has been a recent, popular saying in the industry: to find out if a male star is popular or not, find out if there are fans calling him “wife”. Artists with a tough image often do not make it big, but explode in popularity once they switch to a soft beauty style. Netizens have teased “Ten years as a tough man known by none; one day as a beauty known by all”. This take on aesthetics is influencing visual media creation and entertainment production to a certain extent. Watching from a distance, more and more traffic-generating stars look like “cream young men” [Pie note: 奶油小生, from 奶油 “cream” + 小生, “the role of young men in traditional Chinese opera”, is an old-fashioned term traditionally used to describe young, good-looking actors who often presented as pale, mild-mannered, scholarly]. Some entertainment venture capital picks “flower men” as their choice for leads regardless of the TV dramas/films’ subject matter, follows the young (male) idol path. Commercial products and ads extend their offers to “little fresh meat” [Pie note: 小鲜肉 is the nickname for young (male) idols]. Even cosmetics, which have conventionally been thought of as women-only products, are no longer asking only women stars to be their spokespeople. Feminine beauty can exist, but all things shouldn’t be taken to the extreme. As “flower men” overflow on screen, masculine, tough men are reducing in numbers. This may counter the basic rules of art creation, and disrupt the development of diverse social aesthetics.

Any product produced by the mind, in the process of production, is also producing minds that will accept it, consume it. Audience of Dangai include not only adults, but also not-too-mature youths who pursue “Rot Culture” as a fashionable trend. In particular, as the aesthetics of men in the eyes of young women turn even more feminine, such change can indirectly influence the cognition of young men, cause the young men to subconsciously shift their own gender expression closer to the feminine beauty anticipated by women. Most Dangai stories are far removed from reality; some young audience nonetheless mix them up with real life, develop biased understanding such as “only love that doesn’t treat matrimony and reproduction as destinations is true love”. Although Daigai is often made “Danmei-less”, in that the romantic relationship between the two male leads are re-written as brothers and zhiji (confidants), the canon and the Rot Culture behind it still hides large amounts of pornographic, violent content, including biased, unhealthy perspectives on gender, and un-scientific, even wrong biological knowledge. If such content isn’t given restrictions, it will seriously mislead the values and self-fulfilment of the young.

PART 1 PART 2 <-- YOU ARE HERE PART 3