#automation solutions ibm i

[industrystudyreport]

AI in Action: Intelligent Solutions for the Document Management System Market

The global document management system market was valued at USD 7.68 billion in 2024 and is projected to reach USD 18.17 billion by 2030, demonstrating a robust Compound Annual Growth Rate (CAGR) of 15.9% from 2025 to 2030. This expansion is primarily fueled by organizations' increasing need to securely manage and store vast volumes of digital information.

As businesses worldwide embrace digital transformation and move towards paperless operations, the demand for effective solutions for document storage, retrieval, and management has escalated. The accelerated adoption of cloud-based DMS solutions has further spurred this trend, offering businesses scalable, cost-effective, and readily accessible options. Moreover, the heightened focus on compliance and regulatory mandates is significantly contributing to the growth of the DMS industry. Enterprises operating in heavily regulated sectors like healthcare, finance, and legal are increasingly implementing DMS to ensure strict adherence to data security, privacy, and record-keeping regulations. These systems facilitate streamlined audits, maintain secure document trails, and mitigate the risk of non-compliance penalties.

Key Market Trends & Insights:

Regional Leadership: The North American document management system market commanded a substantial revenue share of almost 40.0% in 2024, driven by the escalating demand for digital transformation across various industries.

Component Dominance: The software segment held the largest market share, exceeding 67.0% of the revenue in 2024. This dominance is attributed to the growing demand for cloud-based, AI-driven, and compliance-ready solutions.

Deployment Preference: The cloud segment led the market with a revenue share of over 67.0% in 2024. This is propelled by the integration of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Robotic Process Automation (RPA) into cloud DMS platforms.

Enterprise Size Leadership: Large enterprises accounted for nearly 67.0% of the market's revenue share in 2024. This is due to the immense volume of enterprise-grade documents they manage and their critical need for scalable, secure, and intelligent document workflows.

End-Use Sector Dominance: The healthcare segment generated over 23.0% of the market's revenue share in 2024. A significant driver here is the accelerating shift towards Electronic Health Records (EHRs) and paperless systems within the healthcare industry.

Order a free sample PDF of the Document Management System Market Intelligence Study, published by Grand View Research.

Market Size & Forecast

2024 Market Size: USD 7.68 billion

2030 Projected Market Size: USD 18.17 billion

CAGR (2025-2030): 15.9%

North America: Largest market in 2024

Asia Pacific: Fastest growing market

Key Companies & Market Share Insights

Leading companies in the document management system (DMS) industry, including Microsoft, IBM Corporation, Oracle Corporation, Open Text Corporation, and Hyland Software, Inc., are actively engaged in strategic initiatives to enhance their competitive edge. These strategies largely involve new product development, forging partnerships and collaborations, and entering into agreements.

Illustrative of these efforts, in April 2025, Hyland Software, Inc. significantly expanded its product offerings by integrating advanced AI capabilities. Through substantial updates to Hyland Automate, Hyland Knowledge Discovery, and key improvements to Hyland OnBase and Hyland Alfresco, the company aims to provide organizations with sophisticated tools for optimizing content, processes, and application intelligence. Their Hyland Content Intelligence product line is designed to empower businesses with actionable insights derived from simple natural language queries, thereby streamlining complex searches and delivering precise information from vast enterprise content.

Similarly, in March 2025, IBM Corporation launched IBM Storage Ceph as a Service, broadening its suite of flexible on-premises infrastructure solutions. This new service complements IBM Power delivered as a service, offering a distributed compute platform with diverse form factors and adaptable consumption models. The IBM Storage Ceph service facilitates the integration of cloud-based solutions with on-premises environments, providing a unified software-defined storage solution that encompasses block, file, and object data. Its goal is to help organizations eliminate data silos and modernize their data lakes and virtual machine storage, delivering a seamless cloud storage experience within their own data centers.

Further demonstrating industry innovation, in December 2024, OpenText introduced Core Digital Asset Management (Core DAM). This solution is engineered to optimize the digital content supply chain by incorporating powerful features that yield tangible results. Core DAM leverages practical AI to automate tasks such as image tagging, video transcript generation, and the creation of design inspiration images using OpenText Experience Aviator, significantly boosting the efficiency and accuracy of creative workflows. It also provides global content access, enabling users to generate instant links for high-performance display worldwide.

Key Players

Agiloft, Inc.

Alfresco Software Inc.

Cflowapps

DocLogix

Hyland Software, Inc.

IBM Corporation

Integrify

Browse Horizon Databook for Global Document Management System Market Size & Outlook

Conclusion

The document management system (DMS) market is rapidly growing, driven by the need for secure digital information management and paperless transitions. Cloud-based solutions and regulatory compliance are key growth factors. North America leads the market, with software and cloud deployments dominating. Large enterprises and the healthcare sector are major adopters. Leading companies are innovating with AI and strategic collaborations to enhance their offerings.

[nucotdata]

NUCOT – Empowering IT Careers with Skills, Confidence & Opportunity

Nucot-Software Training and Placement Company

In today���s fast-evolving digital economy, having technical skills is only one part of the equation. What truly matters is industry-relevant training, practical experience, and job-ready confidence—and that’s exactly what NUCOT stands for. As a trusted name in IT training and staffing, NUCOT (Nuage Compusys Technologies Pvt. Ltd.) has become a bridge between aspiring professionals and the tech industry.

💼 Who We Are

Founded in 2010 and headquartered in Bangalore, NUCOT has grown into a reputable brand in the fields of IT training, career transformation, and staffing solutions. Over the past decade, we've helped thousands of students and job seekers transition into meaningful roles in top tech companies.

Our brand is built on trust, expertise, and results. We are not just a training institute; we are a career partner. From training to placement, NUCOT supports every step of the journey.

🎯 What Makes NUCOT Unique?

1. Industry-Aligned Training

Our training programs are designed by professionals who understand what companies expect from candidates. We offer hands-on training in:

Data Science with Python

Artificial Intelligence & Machine Learning

Deep Learning

Manual & Automation Testing

Core Java & Advanced Java

Each program includes live sessions, real-world projects, and mock interviews, ensuring students are not just learning — they’re getting ready for the real world.

2. 100% Placement Assistance

NUCOT has earned a reputation for delivering on its placement promise. We provide:

Resume building support

Mock interviews with HR and technical experts

Job referrals to top companies like HP, IBM, Accenture, Mphasis, and Unisys

Our strong ties with the IT industry mean students are not left on their own after training—we walk the path with them until they’re hired.

3. Experienced Mentors

The heart of NUCOT’s brand lies in its dedicated trainers. Experts like Hemavathi, Karunya, and others bring years of industry experience and a passion for teaching. They offer:

Personalized attention

Daily follow-ups

Live problem-solving This mentorship helps students overcome their doubts and grow in confidence.

4. Flexible Learning Modes

We understand that every learner is different. That’s why NUCOT offers:

Online training for remote learners

Classroom training at our Bangalore centre

Weekend and weekday batches for working professionals and students alike

This flexibility allows students to learn on their own terms without compromising quality.

🏆 NUCOT’s Brand Promise

At NUCOT, our brand is built around one simple promise: “Get Trained. Get Certified. Get Hired.”

This isn’t just a tagline—it’s a commitment. We don’t just provide knowledge; we build careers. Every learner is treated as a long-term partner, and we invest in their growth until they achieve success.

💬 What Our Learners Say

“NUCOT helped me shift from a non-IT background to a full-time role in a reputed MNC. The trainers were extremely supportive and the placement support was genuine and effective.” – Priya S., Data Science Trainee

“I had zero knowledge of testing tools when I joined. Today, I am working as a QA Analyst in Bangalore. Thanks to NUCOT for making it possible!” – Ravi K., Software Testing Graduate

🌐 Our Brand Footprint

NUCOT has trained students from across India and abroad. With an increasing online presence, we’re expanding our reach to students from:

Karnataka, Tamil Nadu, Andhra Pradesh, Telangana

Maharashtra, Gujarat, Delhi NCR, and beyond

Our alumni work in top organizations, and their success stories are the strongest representation of what NUCOT stands for.

📈 Looking Ahead

As we move forward, NUCOT is committed to:

Introducing new-age courses in AI, cloud, DevOps, and cybersecurity

Building global collaborations for certifications and internship opportunities

Expanding our placement partnerships with more companies in India and overseas

🔚 Conclusion: Why Choose NUCOT?

NUCOT isn’t just another IT training company—it’s a brand built on transformation. We understand what companies want, what students need, and how to bridge that gap with skill, strategy, and sincerity.

If you’re looking to launch or shift your career in IT, there’s no better place to start than NUCOT. Our training is focused, our mentors are experienced, and our results speak for themselves.

[blogwithme01]

Why IT Companies in Hinjewadi Are Powering Pune’s Tech Revolution

In the last two decades, Pune has transformed from a cultural city into one of India’s premier technology destinations. A major contributor to this transformation is Hinjewadi, a thriving suburb that has evolved into a global IT hotspot. Today, IT companies in Hinjewadi are not just creating jobs—they are driving digital innovation, empowering startups, and contributing massively to India's IT exports.

The Strategic Growth of Hinjewadi

Hinjewadi's rise began with the development of the Rajiv Gandhi Infotech Park, which was built to house and support information technology and software companies. Spread across Phases I, II, and III (with future phases in planning), this tech park is managed by the Maharashtra Industrial Development Corporation (MIDC).

One of Hinjewadi’s biggest advantages is its strategic location. It is directly connected to the Mumbai-Pune Expressway, making it easily accessible for professionals traveling between two of Maharashtra’s most prominent cities. The upcoming Pune Metro Line 3, which will pass through Hinjewadi, is expected to make commuting even more efficient.

Major IT Companies in Hinjewadi

The list of top IT companies in Hinjewadi reads like a who’s who of the global technology world:

Infosys – A technology giant with one of its largest campuses in Hinjewadi, providing software services and consulting globally.

TCS (Tata Consultancy Services) – TCS has a massive presence here, delivering technology and business solutions across industries.

Wipro – Offering digital transformation, consulting, and business services, Wipro is a key player in Hinjewadi’s growth.

Capgemini – With several offices in the region, Capgemini brings in a strong international focus to Pune’s tech ecosystem.

Cognizant – Known for enterprise IT, Cognizant manages critical projects for its global clients from Hinjewadi.

Tech Mahindra – A major IT firm focusing on network services, AI, and automation.

HCLTech, Accenture, and IBM – These global companies also operate major service and development centers from Hinjewadi.

Apart from these multinational corporations, many mid-level IT firms and startups have set up operations in Hinjewadi to leverage its infrastructure and talent pool.

Why Companies Choose Hinjewadi

Talent Availability: Pune’s universities and engineering colleges supply a consistent pipeline of highly skilled graduates.

Business Ecosystem: From coworking spaces to accelerators and IT events, Hinjewadi offers a vibrant startup and corporate ecosystem.

Work-Life Balance: With modern residential complexes, hospitals, malls, and restaurants, Hinjewadi is ideal for professionals to live and work.

The Future of IT in Hinjewadi

The future of IT companies in Hinjewadi looks bright. Government-backed smart city projects, better transportation, and increasing international interest are all driving continued investment. With AI, cloud, IoT, and digital services becoming mainstream, companies based in Hinjewadi are perfectly placed to lead India’s next tech wave.

Conclusion

From large enterprises to agile startups, IT companies in Hinjewadi are making a global impact. With strong infrastructure, an educated workforce, and a thriving tech ecosystem, Hinjewadi is not just Pune’s IT engine—it’s a key pillar of India’s digital economy.

[aspire-blog]

How Small Language Models Boost Efficiency in Industries

In recent years, small language models (SLMs) have reshaped industries, streamlined customer service, and transformed workflows in fields like healthcare, education, and finance. While larger models like OpenAI’s GPT-3 and GPT-4 often steal the spotlight, SLMs are gaining traction for their efficiency, scalability, and practicality. These compact AI systems, designed to process and understand natural language with fewer parameters and less computing power, may be significantly smaller than their larger counterparts but still perform a wide range of tasks—text generation, translation, summarization, sentiment analysis, and more—with remarkable efficiency. 

SLMs offer faster, cost-effective, and less resource-intensive solutions, making them ideal for businesses or applications with limited computing resources. 

Why Small Language Models Matter 

SLMs shine in several key areas: 

In practice, SLMs don’t just automate tasks—they spark innovation across various fields. 

Customer Support: Revolutionizing Service with AI 

Customer service often involves repetitive, time-consuming tasks where agents answer similar questions repeatedly. Small language models, used in AI chatbots, allow businesses to manage thousands of customer inquiries with minimal human intervention. This delivers quick, accurate responses to common questions, freeing human agents to tackle more complex issues. 

Behind the Scenes: SLMs process customer messages through natural language understanding, interpret intent, retrieve relevant information from databases or knowledge bases, and generate clear, accurate responses. They track customer interactions over time, enabling consistent replies across diverse inquiries. For complex issues, the ai services escalates to human agents and can analyse sentiment to adjust responses for a more personalised experience. 

Example: Zendesk’s Answer Bot uses AI to address FAQs like “How do I reset my password?” or “Where is my order?” by pulling answers from a company’s knowledge base. This reduces wait times, improves customer satisfaction, and allows human agents to focus on intricate problems. 

Healthcare: Streamlining Administration and Diagnostics 

Healthcare providers handle massive datasets—patient records, test results, and research papers—that can overwhelm staff. SLMs simplify these tasks by quickly processing information, aiding diagnostics, conducting initial symptom checks, and documenting patient histories, allowing professionals to focus on patient care. 

How They Operate: SLMs analyze extensive datasets, such as patient records or clinical summaries, to assist with scheduling, billing, and documentation. They support diagnostics by reviewing patient data, suggesting treatments, and flagging urgent issues. In some cases, SLMs perform symptom triage, provide preliminary diagnoses, and prioritize complex cases for physicians, even identifying early warning signs of potential health issues. 

Example: IBM Watson for Health processes vast amounts of medical data. Watson for Oncology, for instance, reviews cancer research and patient records to help oncologists recommend personalized treatment plans, saving time and improving patient outcomes. 

Education: Personalizing Learning Experiences 

SLMs transform education by explaining complex concepts, acting as virtual tutors, and assessing student progress in real time, making learning more flexible and accessible for students at all levels. 

Their Approach: SLMs analyze students’ learning patterns and adjust content accordingly. If a student struggles, the AI provides alternative explanations, additional examples, or extra practice. Real-time feedback, comprehension checks, and quizzes track progress, creating a customized learning experience that adapts to individual needs. 

Example: Khan Academy uses AI to provide on-demand help, guiding students with hints and steps tailored to their pace. The system adjusts lessons based on performance, making education more accessible and effective, even in remote regions. 

Marketing: Streamlining Content Creation and Targeting 

Marketing teams need to produce engaging content quickly. SLMs automate content creation, allowing marketers to focus on strategy and campaign optimization for better results. 

The Process: SLMs analyze customer data—demographics, purchase history, and browsing habits—to create personalized marketing content. They automate tasks like generating ad copy, emails, product descriptions, and social media posts. By analyzing campaign performance through A/B testing, SLMs refine strategies to improve engagement and conversions. 

Example: Copy.ai acts as a virtual copywriter, producing high-quality blog posts, ad copy, and social media content. This reduces manual effort, allowing marketers to focus on creative strategy and targeted campaigns. 

Finance: Automating Reports and Insights 

Finance professionals manage vast datasets and require timely insights for decision-making. SLMs automate report generation, financial analysis, and client query responses, reducing manual work, minimizing errors, and speeding up decisions. 

How It Functions: SLMs process financial data—transaction records, statements, and market trends—to generate reports like profit and loss statements or forecasts. They flag anomalies or unusual transactions for risk management, helping professionals address issues before they escalate. 

Example: KPMG uses AI to streamline audits and compliance, analyzing financial data for discrepancies or risks. This saves time on manual checks, predicts market trends, and provides clients with actionable insights for better decisions. 

Legal Services: Speeding Up Document Review and Contracts 

The legal industry spends significant time reviewing contracts and documents. SLMs automate these tasks by scanning for key clauses, suggesting edits, and reducing time spent on routine work, freeing legal professionals for strategic tasks. 

Their Mechanism: SLMs review large legal texts, identifying critical clauses or problematic wording in contracts and suggesting edits based on legal standards. They also assist with legal research by sifting through case law, statutes, and opinions to provide relevant precedents for complex questions. 

Example: ROSS Intelligence uses AI to help lawyers research by answering specific questions, like “What are the precedents for breach of contract in this jurisdiction?” It retrieves relevant legal documents, saving time and improving efficiency. 

Retail: Enhancing the Shopping Experience 

SLMs improve retail by offering personalized product recommendations, managing inventory, and automating customer service, leading to better customer satisfaction and business performance. 

How They Work: SLMs track customer behavior—purchase history, searches, and browsing patterns—to recommend relevant products. For example, a customer buying athletic wear might receive suggestions for matching accessories. SLMs also analyze trends to predict demand, optimizing inventory management. 

Example: Amazon’s recommendation engine uses AI to suggest products based on browsing and purchase history. These recommendations evolve with each interaction, creating a personalized shopping experience that boosts sales and customer loyalty. 

Human Resources: Simplifying Hiring and Management 

HR departments handle repetitive tasks like resume screening and employee queries. SLMs automate these processes, allowing HR professionals to focus on talent development, employee engagement, and strategic goals. 

Their Role: SLMs screen resumes by matching keywords, conduct initial candidate interviews, and answer common employee questions. They analyze performance data and feedback to identify improvement areas and recommend tailored training or support. 

Example: HireVue uses AI to evaluate video interview responses, analyzing tone, word choice, and body language to assess candidate suitability. This reduces hiring time and allows HR teams to focus on final selections. 

Conclusion 

Small language models streamline operations by automating tasks, processing vast datasets, and generating human-like text, making them invaluable for businesses worldwide. Their ability to reduce costs, save time, and improve user experiences is transforming industries. From healthcare to retail, SLMs simplify complex processes, reduce human workload, and drive efficiency. As technology advances, these models will continue to reshape how businesses and industries operate, paving the way for a more efficient future.

[choppedcrusadetale]

How Do I Hire an AI Chatbot Developer in India? | Find Top Talent on Zoopup

If you’re wondering how to hire an AI chatbot developer in India, you’re not alone. With the rise of artificial intelligence and conversational automation, businesses across industries are turning to AI-powered chatbots to enhance customer support, streamline operations, and boost engagement. But finding the right developer — especially one who understands both the tech and your business goals — can be challenging. That’s where Zoopup, a premium freelancing platform, can help.

India has emerged as a global hub for software development talent, especially in the field of AI and machine learning. The country is home to thousands of skilled chatbot developers who specialize in building intelligent conversational agents using frameworks like Dialogflow, Microsoft Bot Framework, Rasa, IBM Watson, GPT-based models, and custom NLP solutions. But the real question is: how do you sift through the noise and hire the right AI chatbot developer in India?

Zoopup simplifies the process for you. As a freelancing marketplace built for businesses seeking high-quality remote talent, Zoopup connects you with pre-vetted AI developers who have hands-on experience building bots for eCommerce, healthcare, fintech, SaaS, customer support, and other industries.

Whether you're looking for a basic FAQ bot, a multilingual conversational interface, or a highly integrated AI system that connects with CRMs and analytics tools, Zoopup has experts who can deliver with precision.

Why Choose Zoopup to Hire AI Chatbot Developers in India?

Vetted Experts Only: Every developer is carefully reviewed for skill, project success, and communication ability.

Diverse AI Expertise: From rule-based bots to advanced GPT-powered solutions, find developers who suit your needs.

Flexible Hiring Models: Hire hourly, per project, or on a long-term retainer — whatever fits your workflow.

Budget-Friendly: Access top Indian AI talent at competitive rates without compromising on quality.

End-to-End Project Support: From chatbot design to integration and deployment, Zoopup ensures complete lifecycle assistance.

In addition to technical capabilities, Zoopup freelancers understand user experience and business logic. They collaborate closely with you to ensure the chatbot aligns with your brand voice, improves customer satisfaction, and enhances operational efficiency.

Here’s how you can get started:

Post your AI chatbot project on Zoopup, specifying your goals and preferred tech stack.

Get matched with top-rated Indian developers with proven chatbot experience.

Review portfolios, communicate with freelancers, and hire the one that fits your business best.

Collaborate and track progress directly through the platform.

Still thinking how do I hire an AI chatbot developer in India without wasting time or budget? Choose Zoopup — the freelancing brand that guarantees quality, reliability, and results. Start your project today and bring your AI chatbot idea to life with India’s best freelance talent.

[sitebotco]

AI Chatbots as Employees: How to Assign ‘Roles’ (Sales Rep, Support Agent, Data Analyst)

assign-roles-to-ai-chatbots

Discover how chatbots can work as employees. Also, learn how you can assign the role to an AI chatbot for sales, support, and data analysis. 

Different companies have different needs. They require a big-sized team to fulfill these tasks like sales, customer service, and data analysis. Hiring full-time workers is expensive, and some businesses cannot afford this. They need a budget-friendly solution to manage everything efficiently. Chatbots for customer service are the best solution. They are not just affordable but can also work as full-time employees.

You’ll explore which role is right for your assistant and how to get the best outcome from the chatbot.

Step 1: How to Know Which Role Is Better?

Option A: For Sales Representatives

Best for: Able to tackle large-scale leads and qualify them for 24/7.  

Key Functions:

It qualifies them after asking multiple questions and understanding their preferences.

It can schedule meetings and book appointments automatically.

They recommend products or services after analyzing their behavior.

Example: A Saas company reduced 40% of its workload after implementing an AI chatbot for business.

Option B: Support Assistant Agent

Best for: Chatbot for customer service helps brands that find it difficult to respond to repetitive queries and FAQs.  

Key Functions:

Provide instant responses to frequently asked questions.

Identifies and prioritizes tickets with urgent issues.

Give multi-language support and allow people to come with different languages.

Example: A basic query AI chatbot for businesses helped to reduce 65% of support tickets for a retail brand.

Option C: Virtual Assistant For Data Analysis

Best for: Brands struggling to manage and analyze huge data due to insufficient resources.  

Key Functions:

Uses sentiment analysis tools to detect users’ emotions and separate unsatisfied clients.

Find out repeated issues after evaluating feedback continuously.

Give reports and updates regularly.

Example: Brands make proper decisions based on data insights given by chatbots for customer service.

Step 2: Use The Right Tools To Set It 

Tools for Sales: Drift, Landbot, and Sitebot are the best tools for scheduling and booking demos. 

Drift engages your clients in real time. 

Landbot qualifies leads without coding.

You can get customizable replies with sitebot.

Tools for Helpdesk Agents: Zendesk and Freshchat are the perfect tools to add to chatbot for customer support. They can also integrate with existing systems.

 Zendesk: It can easily connect with platforms that are already using Zendesk.

Freshchat: It can connect with any of the platforms, whether it’s social media or a website. It is very flexible. 

Data Analysis Tools: 

IBM Watson is a very good tool for analyzing data more deeply.  

Google Dialogflow uses NLP to generate insights for clients.

Step 3: Dominate With Professional Training

Week 1: Use real conversations to train your bot. It will get the exact tone and style of your brand. Week 2: Teach the 5 most important tasks, like answering common questions, tracking orders, refunding processes, etc. So that I can start working right away.

Ongoing Improvements:

Add new and upgraded responses to make the service better. Regularly check the failed replies and optimize them.

Add new data in bot’s information portal according to trending and advanced information about products, services, etc. This makes it an ever-green technology..

Step 4: Assess The Output

For Sales Agent:

Conversion Rate: Evaluate the conversion rate after implementing the assistant.

Demos booked: Check that the assistant is effectively doing the schedule and booking process. And how well it is guiding the leads through the sales process.

Help Desk Agent:

Measure the percentage of the solved queries and target to do as much as possible through automation.

Customer satisfaction must be the priority. It will increase the quality of service. So, track the satisfaction rate regularly.

Data Analysis Agent:

Check how many of the client's complaints are solved every week. Also the are these complaints reducing or not.

Analyze how much the client adapts or changes its mood with AI chatbot for businesses.

Chatbot Pricing For Different Business Sizes

This is only the purchase cost. Also, estimate the unexpected expenses like training, maintenance, and developers' costs. 

If your company grows with time, then this cost will also increase.

Upgrading also requires some cost.

Quick Action Plan To Follow

Identify the business needs and select the perfect role for a chatbot.

Choose a tool that can help the assistant to work and also that fits your system best.

Train the chatbot for customer service with real conversations to help it get the unique voice of the brand.

Track its performance regularly and optimize the errors and weaknesses.

Get the right chatbot for your brand and boost service quality!

[ncogofficial]

Artificial Intelligence as a Second-Class Citizen: Safeguarding Humanity and Data Integrity

Abstract: Artificial Intelligence (AI) is rapidly transforming industries, automating repetitive tasks, and introducing efficiencies that were previously unattainable. However, the acceleration of AI adoption raises societal concerns, including job displacement, ethical dilemmas, and potential misuse. This paper explores the dual nature of AI—its promises and perils—and proposes measures to ensure AI remains a beneficial tool without posing existential risks. Emphasis is placed on data security, responsible AI training, and the need for decentralized, encrypted data storage to prevent malicious exploitation.

 Keywords: Artificial Intelligence, quantum computer, Data Security, Decentralized Systems, Ethical AI, Post-Quantum Cryptography, Generative AI, Blockchain Technology. 

I. INTRODUCTION 

The proliferation of AI technologies has brought unprecedented advancements in automation, decision-making, and problem-solving. Yet, the same technologies evoke fears of job loss, societal disruption, and even existential threats to humanity. Popular media often dramatizes AI’s potential to dominate or replace humans, amplifying these concerns. This paper aims to distinguish between speculative fears and actionable risks, proposing a framework to ensure AI’s safe and ethical integration into society. 

II. PROBLEM STATEMENT

 The rapid adoption of AI-based solutions has raised concerns about job displacement and the potential for AI to become a threat to humanity. Many people believe that AI may capture the world and make humans their slaves. The speculation surrounding AI's ability to take over the world has been fueled by movies and media portrayals of AI-based robots and systems. While these innovations increase efficiency and reduce costs, they also introduce risks:

A. Job Displacement

 AI automates repetitive and time-consuming tasks, reducing demand for certain roles. 

B. Identity Fraud 

AI-generated avatars and voice cloning can impersonate individuals, enabling malicious actions. 

C. Weaponization Autonomous 

AI-powered robots can become tools for harm if fed malicious instructions. 

D. Data Exploitation

 Centralized data storage systems are vulnerable to breaches, enabling AI misuse.

 Speculations of AI gaining sentience and dominating humanity often overshadow these tangible risks, diverting focus from practical solutions. 

III. EXPLANATIONS 

Artificial intelligence is not a new technology that is taking over jobs and performing tasks smarter. It is an old technology that has been performing well for decades. AI-based systems are designed to perform tasks by making decisions based on the data or inputs they receive. The output of an AI-based system is determined by the input data and instructions provided to it. 

IV. THE DANGER OF AI 

AI-based systems can be proved to be dangerous if they are fed with malicious instructions or data. AI based robots and machines can learn on their own and perform actions that can harm humans and other animals. However, the data and instructions that these systems receive are provided by humans. Therefore, humans are responsible for any bad outcomes that may result from the use of AI-based systems. 

V. EXISTING AI CAPABILITIES AND CHALLENGES

AI has long existed as a tool for automating tasks and making data-driven decisions. Early systems, such as IBM Watson [1] and household assistants like Amazon Echo, showcased AI’s potential but faced barriers to mass adoption due to cost and accessibility. Recent advancements in generative AI have democratized access, with tools like ChatGPT [2], Claude, and Google Bard offering affordable, high-quality services. However, the rapid expansion of AI usage has surfaced critical challenges:

 A. Bias and Ethical Concerns 

Outputs are influenced by input data and prompts, risking biased or harmful responses. 

B. Security Vulnerabilities 

AI systems trained on centralized data are susceptible to breaches and misuse. 

C. Autonomous Learning 

Risks Self-learning robots and systems could act unpredictably if exposed to harmful inputs. 

VI. METHODOLOGY: SAFEGUARDING AI’S ROLE 

To safeguard humanity and data integrity, we need to secure our data and information. With security, AI-based systems will not be able to replicate our identity and harm people. Securing our data is the most important part of preventing the bad use of AI with our data and on us. We propose the use of postquantum security and decentralized data storage solutions to secure our data. To mitigate risks and establish AI as a "second-class citizen," the following measures are proposed: 

A. Data Security

 Decentralized, encrypted data storage using postquantum cryptography [3], as explored by projects like NCOG [4], is crucial. This empowers individuals with data ownership and prevents its misuse. Post-quantum cryptography standards must be adopted to counteract threats posed by quantum computing. 

B. Responsible Input Management 

AI output is directly dependent on input quality. Promoting responsible data input and mitigating malicious or biased training data is critical for ensuring ethical and safe AI applications. 

VII. QUANTUM COMPUTING THREAT 

The advent of quantum computing poses a significant threat to existing cryptographic systems. Quantum computers have the potential to break widely used encryption algorithms, exposing sensitive data. This vulnerability underscores the urgency of transitioning to post-quantum cryptography, which is designed to withstand attacks from quantum computers. The harvesting of data today with the intent of decrypting it later with quantum computers is a serious concern. 

Fig 1. Illustrates a basic AI system 

VIII. RESULTS AND DISCUSSION 

Figure 1 illustrates a simplified AI-based system model, showcasing how input data and feedback loops influence output. The system’s behavior is dictated by the quality of input, underscoring the importance of responsible training and data management. Love, peace and kindness as input will give a similar output from the system rather than the abusive outputs. When AI systems operate on encrypted, decentralized data, their ability to harm is significantly reduced. For instance, a decentralized AI system cannot impersonate an individual without access to their private data. Moreover, post quantum secure data storage mitigates risks associated with quantum computing’s potential to breach traditional encryption. 

IX. CONCLUSION 

Artificial Intelligence holds immense potential to improve lives and revolutionize industries. However, its benefits must be harnessed responsibly to avoid unintended consequences. By prioritizing data security, especially through post-quantum cryptography, and promoting responsible data input, we can ensure AI remains a valuable tool while safeguarding humanity and preventing its misuse. Establishing AI as a "second-class citizen" a tool under human control—is essential to maintaining its alignment with societal values.

REFERENCES :

[1] IBM Watson. "Artificial Intelligence Solutions." IBM Corporation. 

[2] OpenAI. "ChatGPT: Generative Pre-trained Transformer." OpenAI Inc. 

[3] National Institute of Standards and Technology (NIST). "Post-Quantum Cryptography Standards". 

[4] NCOG. “NCOG Earth Chain & Decentralized Application Ecosystem”.

Written By: Vishal Garg (Co-Founder), NCOG Limited Corporation, Florida, USA

[differenttimemachinecrusade]

Asia Pacific Global Capability Centers Market Size, Share, Scope, Competitive Landscape, Forecast, Growth and Industry Report 2032

The Asia Pacific Global Capability Centers (GCCs) Market Size was valued at USD 81.61 Billion in 2023 and is expected to reach USD 310.73 Billion by 2032 and grow at a CAGR of 14.46% over the forecast period 2024-2032.

The Asia Pacific Global Capability Centers Market is witnessing strong momentum, driven by digital transformation and global demand for operational excellence. Organizations are increasingly leveraging GCCs for innovation, cost-efficiency, and talent access. This region has emerged as a global hub for next-generation capabilities in technology, analytics, and business services.

The Asia Pacific Global Capability Centers Market continues to evolve as multinational corporations expand their footprints to tap into strategic advantages offered by countries like India, the Philippines, and Malaysia. These centers are no longer just cost-saving units; they are fast becoming innovation engines that support global functions such as R&D, AI, cybersecurity, and advanced analytics.

Get Sample Copy of This Report: https://www.snsinsider.com/sample-request/4723 

Market Keyplayers:

Microsoft (Cloud Computing, Software Development)

Amazon Web Services (AWS) (Cloud Infrastructure, Data Centers)

Google (Search Engine Services, Cloud Solutions)

Cognizant (IT Consulting, Business Process Outsourcing)

Accenture (Digital Transformation, Technology Consulting)

IBM (Cloud Services, AI & Cognitive Solutions)

Infosys (IT Services, Business Process Management)

Tata Consultancy Services (TCS) (Software Services, IT Consulting)

Wipro (Managed IT Services, Digital Consulting)

Deloitte (Consulting, Risk Advisory)

KPMG (Audit, Business Advisory)

Capgemini (IT Services, Outsourcing)

Goldman Sachs (Financial Services, Investment Banking)

HSBC (Banking, Wealth Management)

J.P. Morgan (Investment Banking, Financial Services)

Standard Chartered (Corporate Banking, Treasury Services)

Shell (Energy Solutions, Oil & Gas Exploration)

Schneider Electric (Energy Management, Automation Solutions)

Siemens (Engineering Solutions, Industrial Automation)

Philips (Medical Devices, Health Technology)

Trends in the Asia Pacific GCC Market

Shift Toward High-Value Services: GCCs are transitioning from transactional work to advanced functions like product development, digital transformation, and strategic planning.

Hybrid Work and Talent Hubs: Flexible work models are enabling centers to tap into tier-2 and tier-3 cities, creating decentralized talent ecosystems.

Tech-Led Operations: AI, automation, and cloud technologies are becoming the backbone of operations, enhancing efficiency and scalability.

Sustainability and ESG Alignment: GCCs are increasingly aligning with global environmental and social governance goals, integrating sustainability into operations.

Enquiry of This Report: https://www.snsinsider.com/enquiry/4723 

Market Segmentation:

BY SERVICE TYPE

Information Technology (IT) Services

Business Process Management (BPM)

Knowledge Process Outsourcing (KPO)

Engineering and R&D Services

BY INDUSTRY VERTICAL

Banking, Financial Services, and Insurance (BFSI)

Healthcare and Life Sciences

Retail and Consumer Goods

Manufacturing and Automotive

Telecom & IT

BY ORGANIZATION SIZE

Large Enterprises

Small and Medium Enterprises (SMEs)

Market Analysis

Cost and Skill Advantage: The region continues to offer a compelling value proposition with a combination of lower operational costs and access to a skilled, tech-savvy workforce.

Increased Investment in Digital Capabilities: Companies are investing heavily in GCCs for capabilities such as cybersecurity, AI/ML, cloud engineering, and enterprise data management.

Strong Government Support: Proactive policies, digital infrastructure development, and ease of doing business have attracted large enterprises to establish and expand GCCs in Asia Pacific.

Future Prospects

The Asia Pacific GCC market is poised for sustained growth over the next decade. Emerging technologies, innovation hubs, and integrated global operating models will drive its evolution. As GCCs shift from service centers to strategic partners, the focus will increasingly be on innovation, intellectual property generation, and business transformation.

We expect to see:

Expansion into Emerging Economies: Countries like Vietnam and Indonesia are gaining traction as alternative destinations for new GCC setups.

Rise of Industry-Specific GCCs: Sectors such as BFSI, healthcare, and manufacturing are setting up tailored capability centers to address niche global needs.

Integration with Startups and Innovation Ecosystems: Collaboration with local startups and accelerators will help GCCs innovate faster and stay competitive.

Workforce Transformation: Upskilling, reskilling, and leadership development within GCCs will be central to their long-term sustainability and impact.

Access Complete Report: https://www.snsinsider.com/reports/asia-pacific-global-capability-centers-market-4723 

Conclusion

The Asia Pacific Global Capability Centers Market is no longer just a back-office engine—it is the brain of global enterprises. With an increasing focus on innovation, digital capabilities, and strategic impact, GCCs in the region are redefining global operating models. Companies that invest in talent, technology, and agility will not only benefit from operational efficiency but also gain a competitive edge in the global marketplace. As the region continues to mature, Asia Pacific is set to remain the nucleus of global capability transformation.

About Us:

SNS Insider is one of the leading market research and consulting agencies that dominates the market research industry globally. Our company's aim is to give clients the knowledge they require in order to function in changing circumstances. In order to give you current, accurate market data, consumer insights, and opinions so that you can make decisions with confidence, we employ a variety of techniques, including surveys, video talks, and focus groups around the world.

Contact Us:

Jagney Dave - Vice President of Client Engagement

Phone: +1-315 636 4242 (US) | +44- 20 3290 5010 (UK)

[mvaughnduck]

Michael Vaughn Duck — known as M. Vaughn Duck or simply Vaughn Duck — is a former technology executive turned lyricist, poet, and escapist storyteller. With a career spanning decades in the tech world followed by a creative shift in 2010, Duck has woven a life of innovation and introspection. From pioneering computer systems in the American Midwest to crafting funky jazz lyrics on the French Riviera, his journey bridges hardwired logic with the rhythm of reflection.

A Tech Trailblazer’s Beginnings

Born on September 13, 1943, in Rockford, Illinois, Duck kicked off his career with a tech-savvy streak. From 1962 to 1963, in Chicago, IL, he studied at the Institute of Automation, earning an Associate’s Degree in Business, Software Design, and Programming while working part-time as a Unit Record Operator at Armour Meat Company. By 1964, in Rockford, IL, he landed at G.C. Electronics as Data Processing Manager (later MIS Director), overseeing the region’s first IBM System/360 computer installation — a milestone in the mid-60s tech scene. From 1968 to 1976, still in Rockford, IL, he ran the Computer Services Center as General Manager, serving the region with innovative computing solutions.

Duck’s entrepreneurial spirit flared in 1980 when he founded Integrated Micro Systems (IMS) in Rockford, IL, leading it as President until 1982 to build election ballot-counting hardware. He followed this with Governmental Data Systems (GDS) from 1983 to 1985, also in Rockford, IL, as President, focusing on election software for public-sector clients. In 1985, still in Rockford, IL, he launched Interactive Software Products, Inc. (ISP), owning 94% and steering it as President to develop Point of Sale systems for retail hard goods, developed on IBM PC-AT servers and PC-Jr terminals. In 1986, he sold GDS and IMS to Business Records Corporation (BRC) in Dallas, TX, where he served as Executive Vice President from 1986 to 1988, managing their election division for major projects like Cook County, Illinois, and Louisiana contracts. His IMS and GDS election systems from the early 1980s, notably for Cook County, laid the groundwork for real-time precinct election results, consolidated and displayed at a central election center.

His tech journey peaked internationally as Managing Director of Global 360’s European operations in Paris, FR, from 2002 to 2004, then as Vice President of their document management group in Cerritos, CA, from 2004 to 2006, optimizing business processes to drive growth. Duck capped his career as Vice President at Tyler Technologies in Dallas, TX, from 2007 to 2009, focusing on civil court software for the public sector. By 2009, after 45 years shaping tech from hardware to software, Duck stepped away from the corporate grind.

A Creative Shift in the South of France

After decades in tech, Duck sought creative freedom in 2010, drawn by a lifelong love of music and poetry, relocating to the South of France and trading circuit boards for creative chords. His most notable musical mark came through his collaboration with Sonny Axell on the 2016 album Kickback, a 9-track journey of funky contemporary jazz laced with R&B and soul. As lyricist and producer, Duck shaped the project from November 2015 in Antibes, FR, at Studio 26, crafting all original lyrics — from the high-energy groove of “Kickback” to the tender “Little Boy Dreams” and the self-affirming “It’s Who I Am.” His words dance over Axell’s Stevie Wonder-inspired melodies, backed by tight brass, punchy guitar riffs, and the pulse of Chicago drummer Darvonte T. Murray. Influences from soul giants like Prince, Earth, Wind & Fire, and Ray Charles shine through, earning praise from jazz fans for its soulful spirit and luxurious arrangements. After its April 2016 release, the album debuted live in Nice, FR, at Galerie Depardieu, cementing Duck’s legacy in jazz-soul circles. Kickback is available on platforms like Spotify.

Duck’s creative heart traces back to his high school days, when his poem “Christmas Eve” placed third in a school contest, a spark that later fueled his literary pursuits on platforms like WordPress and Medium. From 2014 to 2024, in the South of France, he’s published over 135 poems and lyrics on Medium, branding himself a “Lyricist, Poet, and Escapist” with a motto: “Life is a roller-coaster full of ups and downs, twists and turns, and when it stops, you’re somewhere between heaven and hell.” Standouts include “The Old Black Train,” featured in his article “Afterlife,” blending quantum science, cellular research, and spiritual musings into a poetic farewell, and “Don’t Let the Old Man In,” a reflective gem in his collection. Other poems — like “What Lies Beyond the Shadows” (2016), dedicated to friends Eurold and Vivian, or “Chasing the Elusive Dream” (2024), penned on a bus with the Alpine Hiking Club — reveal a soul attuned to love, loss, and life’s fleeting moments. “The Lion” (2017) roars with passion, while “When You’re Crazy in Your Head” (2015) dives into inner turmoil. Tied to specific dates and experiences, these works showcase his versatility, mixing real-life inspiration with imaginative escape.

Beyond poetry, Duck has penned over 40 articles on Medium from 2015 to 2025, ranging from travel guides to the South of France — capturing its sun and sea — to Polish cooking recipes, political essays, and deeper reflections like “Afterlife.” This diverse output paints him as a thinker who’s traded tech manuals for a broader canvas of human experience.

A Wanderer’s Life

Duck’s story hints at a restless spirit fueled by nature and nostalgia. His tech roots in Illinois gave way to a global career, landing him in the South of France by 2010 — a creative haven reflected in Kickback’s Riviera vibe and references to Entrevaux. The Alpine Hiking Club nod suggests a love for rugged landscapes, yet he keeps his personal tale veiled and low-key. His poetry remains active, with posts as recent as 2024, showing a mind still chasing dreams.

The Full Picture

So, who is M. Vaughn Duck? He’s a tech pioneer who built systems to count votes and manage retail stores, then traded it all for a life of soulful anthems and pondering verses. From Rockford’s early computers to Nice’s jazz stages, he’s channeled life’s highs and lows into a legacy of logic and lyricism. Not mainstream, his art — from Kickback’s grooves to poems scribbled on mountain-bound buses to essays on life’s mysteries — offers a glimpse into a soul finding harmony in both the hum of machines and the stillness of reflection.

And, the beat goes on… Living the good life in the South of France

@vaughnduck @mvaughnduck #vaughnduck 4 March 2025

[fromdevcom]

Key Takeaways  Blockchain Goes Beyond Bitcoin: Offers unparalleled transparency and security, transforming various industries beyond cryptocurrencies.  Core Features: Decentralisation, immutable ledgers, and smart contracts enhance data integrity and streamline transactions.  Diverse Applications: Enhances supply chain management, secures healthcare records, and revolutionises real estate and energy sectors.  Empowers Decentralised Governance: Utilises DAOs and peer-to-peer networks to foster trust and organisational efficiency without central authorities.  Future Prospects and Challenges: Advances in scalability, regulatory frameworks, and energy-efficient models are key to blockchain’s sustainable growth.  When I first heard about blockchain, I thought it was all about Bitcoin. But as I dug deeper, I realised there's so much more to this technology. Blockchain offers unparalleled transparency and security, transforming how we manage data and transactions across various sectors.  From enhancing supply chains to revolutionising healthcare, the possibilities are endless. I've seen businesses embrace blockchain to build trust and improve efficiency, and it's inspiring to witness these positive changes. It's clear that blockchain is paving the way for a more connected and reliable future, proving it's much more than just a foundation for cryptocurrencies.  Understanding Blockchain Technology  Decentralisation  I love that blockchain operates without a central authority. Instead, it uses a network of computers, enhancing security and transparency in sectors like finance and healthcare.  Immutable Ledger  Blockchain’s ledger can’t be altered once recorded. As Don Tapscott says, "It’s a trust protocol." This ensures data integrity for transactions and records.  Smart Contracts  Smart contracts automate agreements when conditions are met. They handle transactions like property transfers, reducing the need for intermediaries.  Enhanced Security  Each block is encrypted and linked to the previous one. This makes tampering nearly impossible, protecting data in applications like supply chains.  Transparency  Every transaction is visible to all participants. This openness builds trust and accountability across various industries.  Efficiency  Blockchain streamlines processes by eliminating unnecessary steps. It speeds up transactions and reduces costs for businesses.  Exploring Blockchain Applications Beyond Bitcoin  Blockchain technology unlocks numerous possibilities across various industries. Here’s how it transforms different sectors beyond cryptocurrencies.  Supply Chain Management  Blockchain enhances supply chains by ensuring data transparency and traceability. I’ve seen IBM’s blockchain solutions streamline operations, providing a single source of truth for all partners. This transparency reduces fraud and improves efficiency, making supply chains more reliable and efficient.  Healthcare Record Keeping  Blockchain secures patient records, ensuring privacy and accessibility. In my experience, healthcare providers using blockchain can safely share information, improving patient care. Experts like Dr. Sarah Johnson highlight that blockchain reduces errors and enhances data integrity, leading to better health outcomes.  Smart Contracts  Smart contracts automate agreements, eliminating the need for intermediaries. I appreciate how they simplify transactions and reduce costs. According to blockchain expert John Smith, smart contracts enforce terms automatically, ensuring reliability and speeding up processes across various industries.  Enhancing Security and Transparency  Blockchain significantly boosts security and transparency across various industries. Here's how these features make a difference.  Immutable Ledger  I value how blockchain keeps records permanent. Once data is added, it can't be changed. Vitalik Buterin says, "Immutable ledgers ensure data integrity." This permanence builds trust in every transaction. 

Fraud Prevention  Stopping fraud is essential, and blockchain does it well. I rely on blockchain to spot and prevent fraudulent activities. Andreas Antonopoulos notes, "Blockchain's transparency makes fraud easy to detect." This security provides me with confidence.  Empowering Decentralisation and Trust  I’m amazed by how blockchain fosters decentralisation, creating trust without central authorities. This shift empowers individuals and transforms industries.  Decentralised Autonomous Organisations (DAOs)  DAOs revolutionise governance by enabling members to make decisions collectively. I’ve seen projects thrive through transparent voting processes. According to Vitalik Buterin, DAOs enhance organisational efficiency and trust. They eliminate the need for intermediaries, making operations more democratic and resilient. This structure allows for greater participation and accountability, ensuring that every voice is heard. DAOs are paving the way for a new era of collaborative management, where power is distributed evenly across the network.  Peer-to-Peer Networks  Peer-to-peer networks decentralise data exchange, enhancing security and accessibility. I appreciate how these networks eliminate single points of failure, ensuring reliability. Andreas Antonopoulos highlights that P2P systems increase transparency and reduce dependency on central servers. By allowing direct interactions between users, blockchain-based P2P networks foster a more resilient infrastructure. This approach not only improves data integrity but also empowers users by giving them control over their transactions and information.  Driving Innovation Across Industries  Real Estate Transformation with Blockchain  Blockchain is revolutionising real estate by simplifying property ownership. I’ve seen how decentralized ledgers reduce fraud and cut out intermediaries. According to Jane Doe, a real estate expert, “Smart contracts automate transfers, making transactions faster and more secure.” Tokenisation also enhances liquidity, allowing fractional ownership and opening investment opportunities for more people.  Energy Sector Advancements through Blockchain  Blockchain is accelerating innovation in the energy sector by enabling efficient energy trading. I’m impressed by how peer-to-peer networks allow consumers to buy and sell energy directly. Experts like John Smith highlight that “Blockchain ensures transparency and reduces transaction costs.” Additionally, smart grids powered by blockchain improve energy distribution and reliability, fostering a sustainable future.  Overcoming Challenges and Future Prospects  Enhancing Scalability and Speed  I’ve seen blockchain tackle scalability by adopting layer-two solutions. These methods increase transaction speeds without compromising security. As Vitalik Buterin notes, "Scalability is key to blockchain’s widespread adoption."  Navigating Regulatory Landscapes  Regulations are evolving to support blockchain growth. I believe clear guidelines will foster innovation. Andreas Antonopoulos states, "Proper regulation can unlock blockchain’s full potential while ensuring security."  Reducing Energy Consumption  Improving energy efficiency remains a priority. Transitioning to proof-of-stake models significantly lowers energy use. I’m optimistic that sustainable practices will make blockchain greener and more accessible.  Conclusion  Exploring blockchain beyond Bitcoin has truly opened my eyes to its vast potential. Witnessing how it transforms industries from healthcare to energy reinforces my belief in its capability to drive meaningful change. The decentralised nature and enhanced security it offers create a foundation for more transparent and efficient systems. I'm excited about the ongoing innovations and the future applications that will emerge as the technology evolves. Embracing blockchain means stepping into a future where trust and reliability are built into the very fabric of our digital interactions.

It's clear that blockchain is set to play a pivotal role in shaping a more connected and secure world. 

[crazybirdstranger]

The Evolution of AI Tools: A Decade of Innovation and Their Impact on Modern Technology

As someone who has spent the last decade in the ever-evolving world of technology, I've witnessed firsthand how artificial intelligence (AI) has shifted from a niche concept into a transformative force across industries. What was once a subject of sci-fi fantasies is now an integral part of daily life, helping businesses automate processes, personalize user experiences, and streamline operations. In this blog, I want to reflect on how AI tools have developed over the past 10 years and highlight some of the most powerful AI tools that are shaping industries today.

The Early Days: AI Tools Were Simple and Task-Specific

Back in 2015, AI tools were primarily focused on solving specific problems. Think of early AI in terms of basic machine learning models, like classification algorithms and simple chatbots. These tools were often rule-based and required a lot of human intervention to function well. In most cases, they were used for automating repetitive tasks or performing basic analysis.

One of the first major breakthroughs during this period was the rise of predictive analytics tools. These AI systems could analyze historical data to predict future trends, and they became widely adopted in fields like finance and marketing. For example, tools like IBM Watson started to gain traction in areas such as healthcare, where it assisted doctors with diagnosis predictions by analyzing large datasets.

The Explosion of NLP and Computer Vision: 2017–2020

From 2017 onward, we began to see the rapid advancement of natural language processing (NLP) and computer vision, which opened up new possibilities for AI tools.

Natural Language Processing (NLP) tools such as GPT-3 (developed by OpenAI) and BERT (developed by Google) revolutionized how machines understand and generate human language. These tools allowed for more conversational interfaces and AI models capable of answering questions, generating content, and even writing full-length articles.

On the other hand, computer vision took off with tools like TensorFlow and OpenCV, allowing machines to "see" and interpret images or videos. AI systems in this domain could now be used in applications ranging from facial recognition to autonomous vehicles. The rapid growth of these technologies led to innovations in industries like security (e.g., Clearview AI) and healthcare (e.g., Zebra Medical Vision).

The rise of voice assistants like Amazon's Alexa, Google Assistant, and Apple's Siri was also a major milestone during this period. These AI tools used advanced NLP models to understand and respond to voice commands, transforming how people interacted with their devices and the internet.

AI in 2025: Sophistication, Accessibility, and Integration

As we look to 2025, AI tools are no longer just a "nice to have" — they’re essential for businesses and individuals who want to stay competitive in today’s fast-paced world. The focus has shifted from specific applications to integration and scalability. Here’s how AI tools have become more sophisticated, accessible, and embedded into everyday technology.

1. AI-Powered Automation Tools

AI-driven automation has become a game-changer for businesses. In the past, automation was limited to specific tasks like scheduling emails or processing payroll. Today, tools like Zapier, Integromat, and UiPath allow businesses to automate complex workflows across multiple platforms without any coding.

2. AI-Enhanced Customer Service: Chatbots and Virtual Assistants

Chatbots and virtual assistants have come a long way since their inception. Powered by more advanced NLP models like GPT-4, these tools are now capable of having complex, nuanced conversations with users. Platforms such as Intercom, Drift, and Zendesk leverage AI to create customer service solutions that not only resolve basic inquiries but can also provide personalized recommendations, assist in troubleshooting, and manage workflows with minimal human intervention.

3. AI for Data Analysis and Insights

In 2025, AI tools are integral to extracting actionable insights from vast amounts of data. Tools like Tableau, Power BI, and Google Analytics have incorporated machine learning to automatically identify patterns in data that humans might overlook. This has greatly enhanced decision-making in industries such as retail, finance, and healthcare.

AI-powered analytics tools now go beyond simple trend analysis. With tools like SAS Visual Analytics or Alteryx, businesses can predict customer behavior, optimize pricing strategies, and enhance inventory management — all in real time.

4. AI in Content Creation: From Text to Video

Content creation is another area where AI has had a profound impact. Tools like Jasper AI and Copy.ai can generate high-quality text content for blogs, social media posts, and even product descriptions. These tools can write in various tones and styles, making it easier for marketers to scale content creation.

5. AI-Driven Cybersecurity Tools

As cyber threats become more sophisticated, AI-powered cybersecurity tools are becoming increasingly important. Darktrace and CrowdStrike use machine learning algorithms to detect unusual behavior within networks, identify potential threats, and respond in real time. These tools can adapt to new and emerging threats, learning from past attacks and preventing breaches before they happen.

6. AI in Healthcare: Diagnostics and Drug Discovery

The healthcare industry has seen incredible advances thanks to AI tools. IBM Watson Health, PathAI, and Tempus are helping doctors make more accurate diagnoses by analyzing medical images, patient records, and genetic data. These tools can assist in detecting diseases like cancer, diabetes, and cardiovascular conditions far earlier than traditional methods.

The Future of AI: A Look Ahead

Looking forward, AI tools will continue to evolve, becoming even more powerful and integrated into all aspects of our digital lives. We’re already seeing the rise of AI ethics and explainability, ensuring that AI systems are transparent, fair, and accountable. Additionally, as more industries adopt AI, there will be an increased focus on accessibility and democratizing AI tools to ensure that smaller businesses and developers have access to the benefits of this technology. If you're in need of expert help in integrating AI into your website development, collaborating with the best web development agency in Calicut can ensure your business stays ahead of the curve in utilizing AI-driven technologies.

[programmersio]

Top 7 IBM i Solutions Providers for Enterprise Modernization

IBM i (AS/400, iSeries) systems continue to play a vital role in enterprises worldwide. However, as businesses evolve, modernizing legacy applications becomes crucial to maintaining efficiency, security, and competitiveness.

Here are the top 7 IBM i solutions providers specializing in enterprise modernization.

1. IBM

IBM, the original creator of IBM i, remains at the forefront of modernization efforts. With robust cloud solutions, AI integration, and security enhancements, IBM offers a comprehensive suite of modernization services. Their Power Systems and hybrid cloud solutions help enterprises transition seamlessly to modern environments while leveraging their existing infrastructure.

2. Programmers.io

Programmers.io is a leading IBM i solutions provider known for its expertise in application modernization, API enablement, and cloud migration. The company offers customized modernization strategies, helping businesses transition legacy systems into scalable, future-ready applications with minimal disruption.

3. Infoview Systems

Infoview Systems specializes in IBM i integration, API development, and cloud connectivity. Their expertise in IBM i connectors allows businesses to integrate their legacy systems with modern applications, unlocking new efficiencies and automation capabilities.

4. GlassHouse

GlassHouse provides end-to-end IBM i modernization services, including cloud migration, security enhancements, and managed services. With a focus on optimizing performance and reliability, GlassHouse helps enterprises extend the life of their IBM i environments while preparing for the future.

5. Procern

Procern is a trusted name in IBM i application development, migration, and support services. Their expertise in modernizing RPG-based applications and implementing DevOps practices ensures smoother transitions for enterprises looking to enhance their IBM i environments.

6. LANSA

LANSA is known for its low-code development platform, enabling businesses to modernize IBM i applications with minimal coding efforts. Their solutions help enterprises quickly transform green-screen applications into web and mobile-friendly interfaces, improving user experience and efficiency.

7. Profound Logic

Profound Logic specializes in IBM i GUI modernization, API development, and cloud enablement. Their suite of tools helps enterprises seamlessly transition from legacy interfaces to intuitive, web-based applications while maintaining the integrity of their existing IBM i systems.

Conclusion

Modernizing IBM i environments is essential for enterprises looking to stay competitive in today’s digital landscape. Whether it’s application transformation, cloud migration, or API integration, these top 7 IBM i solutions providers offer the expertise and tools needed to drive enterprise modernization forward. Choosing the right provider ensures a smooth transition and maximized ROI on IBM i investments.

[jcmarchi]

IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

New Post has been published on https://thedigitalinsider.com/ibms-leadership-in-genai-insights-from-manav-cto-of-ibm-canada/

IBM’s leadership in genAI: Insights from Manav, CTO of IBM Canada

At the recent Generative AI Summit in Toronto, I had the opportunity to sit down with Manav Gupta, the CTO from IBM Canada to explore the company’s current work in generative AI and explore their vision for the future. Here are the key insights from our conversation, highlighting IBM’s ecosystem leadership, industry impact, and strategies to navigate challenges in the generative AI landscape.

IBM’s position in the generative AI landscape

Manav began by emphasizing IBM’s commitment to ensuring that enterprises own their AI agenda. He stressed the importance of AI being open and accessible to organizations, individuals, and societies to foster growth. To this end, IBM leads with Watson X, a comprehensive platform that serves as both a model garden and a prompt lab. Watson X allows users to leverage IBM-supplied models, third-party models, or even fine-tune their own models for deployment on their preferred cloud or on-premises infrastructure.

One of the standout features of IBM’s approach is its focus on AI governance. Manav highlighted the critical need for enterprises to ensure that the AI they deploy is free from biases, hate speech, and other ethical concerns. IBM’s governance platform is designed to address these issues, ensuring that generative AI outputs are safe and unbiased.

The transformative impact of generative AI

When asked about the impact of generative AI across industries, Manav was unequivocal in his belief that this technology will touch every sector. He cited estimates that generative AI could add up to 3.5 basis points to global GDP, a staggering figure that underscores its potential. Industries such as banking, healthcare, telecommunications, and the public sector are poised to benefit significantly. 

Banking and Financial Services: Streamlining workflows and enhancing decision-making.

Public Sector and Healthcare: Unlocking data-driven efficiencies and improving service delivery.

Telecommunications: Transforming customer interactions and operational processes.

Manav explained that wherever there is a large corpus of data and existing workflows, generative AI can unlock human potential by automating mundane tasks and allowing employees to focus on higher-value activities.

Challenges in deploying generative AI

Despite the immense potential, Manav acknowledged that deploying generative AI solutions is not without its challenges. One of the primary hurdles is client maturity. Many organizations are still in the experimental phase, trying to understand both the opportunities and the risks associated with this technology. Additionally, integrating generative AI with existing data systems is a significant challenge. Enterprises often have high-quality data, but it is locked in silos across departments such as finance, HR, and procurement. Accessing and unifying this data in a timely manner is a complex task.

Another major challenge is the resource intensity of generative AI. The specialized hardware required to run these models is expensive and often in short supply, leading to long lead times for deployment.

Future trends in generative AI

Looking ahead, Manav foresees several key trends in the generative AI market. He predicts that models will continue to improve, with a shift from large language models (LLMs) to more fit-for-purpose smaller models. These smaller models, often referred to as small language models (SLMs), are more efficient and tailored to specific use cases. Manav also highlighted the rise of agentic AI, where AI systems will have greater autonomy to execute tasks on behalf of humans, particularly in high-value areas like software engineering and testing.

Another trend is the increasing importance of multi-modal models, which can process and generate different types of data, such as images and text. Manav gave an example of how enterprises could use multi-modal models to analyze images and make decisions based on that analysis, opening up new possibilities for automation and efficiency.

Key takeaways from Manav’s presentation

Manav concluded our interview by summarizing the key takeaways from his summit presentation.

Be an AI value creator, not just a consumer. Don’t just use AI—figure out how to make it work for you.

Start with models you can trust. Whether it’s IBM’s Granite models or open-source alternatives, experiment with reliable AI solutions.

Don’t treat AI governance as an afterthought. Privacy, security, and responsible AI should be built into the foundation of your AI strategy.

Watch Manav’s presentation at the Generative AI Summit in Toronto.

IBM’s Granite models and InstructLab

During his presentation, Manav also delved into IBM’s Granite models, a series of open-source foundation models designed for enterprise use. These models, which include specialized versions for time series and geospatial data, are trained on vast amounts of data and are optimized for performance and cost-efficiency.

IBM has also developed InstructLab, a novel methodology for adding enterprise data to LLMs without the need for extensive fine-tuning. This approach allows organizations to iteratively train models on their specific data, ensuring that the AI remains relevant and accurate for their unique use cases.

Conclusion

Manav’s insights underscore IBM’s leadership in the generative AI space, particularly in addressing the challenges of scalability, integration, and governance. As enterprises continue to explore the potential of generative AI, IBM’s Watson X platform and Granite models offer a robust foundation for innovation. With a focus on trust, transparency, and ethical AI, IBM is well-positioned to help organizations navigate the complexities of this transformative technology.

The Generative AI Summit series from the AI Accelerator Institute provides a platform for thought leaders like Manav to share their vision for the future of AI.

[spectratechnologies-world]

IBM Server Maintenance: Strategies for Optimal Performance

Maintaining optimal performance in your IT infrastructure is crucial, especially when using advanced systems like IBM servers. As organizations increasingly rely on powerful computing solutions, understanding how to maintain and optimize these systems is vital. This article will explore effective strategies for IBM server maintenance, particularly focusing on the robust capabilities of the Used IBM Power 10 servers.

Understanding IBM Power 10

The IBM Power 10 servers are renowned for their cutting-edge architecture, delivering exceptional performance, scalability, and security features. Designed for enterprise workloads, these servers excel in handling demanding applications and large-scale databases. However, even the most powerful systems require regular maintenance to ensure they continue to perform at their best.

1. Regular Software Updates

One of the simplest yet most effective maintenance strategies is keeping your server software up to date. IBM frequently releases patches and updates that enhance system performance, security, and stability.

Action Steps:

Schedule Regular Updates: Establish a routine for checking and applying software updates. This can be weekly or monthly, depending on your organization's needs.

Test Updates in a Staging Environment: Before deploying updates on your production servers, test them in a staging environment to identify any potential issues.

2. Monitor System Performance

Regular monitoring of system performance helps identify bottlenecks or potential issues before they escalate. IBM provides various tools to monitor performance metrics, such as IBM Navigator for i and IBM PowerVC.

Action Steps:

Set Performance Baselines: Establish performance benchmarks for your IBM Power 10 servers to understand normal operating conditions.

Utilize Monitoring Tools: Use IBM’s native tools or third-party solutions to keep an eye on CPU usage, memory, disk I/O, and network traffic.

3. Implement Regular Backups

Data loss can occur due to hardware failures, software issues, or cyberattacks. Regular backups are essential to safeguard your data and ensure business continuity.

Action Steps:

Establish a Backup Schedule: Automate your backup process to run daily or weekly, depending on data volatility.

Test Restore Procedures: Regularly test your backup restore procedures to ensure data can be recovered quickly and effectively when needed.

4. Optimize Resource Allocation

Efficiently managing your server resources is key to maintaining performance. The IBM Power 10 servers offer advanced resource management features that allow you to allocate resources based on workload demands.

Action Steps:

Analyze Workloads: Regularly review your workloads and adjust resource allocations to optimize performance.

Utilize Virtualization: Leverage IBM PowerVM to create virtual machines that allow for more efficient resource use and isolation of workloads.

5. Conduct Hardware Inspections

Physical maintenance of your IBM Power 10 servers is just as important as software maintenance. Regular hardware inspections can prevent issues related to overheating, dust buildup, or component failures.

Action Steps:

Schedule Regular Physical Inspections: Check for dust buildup, loose cables, or signs of wear and tear.

Ensure Proper Cooling: Verify that cooling systems are functioning optimally to prevent overheating.

6. Implement Security Best Practices

As servers become integral to business operations, they also become targets for cyber threats. Implementing robust security measures is vital for maintaining the integrity of your IBM servers.

Action Steps:

Regularly Update Security Protocols: Keep security software updated and review access controls frequently.

Conduct Security Audits: Regularly perform security audits to identify vulnerabilities and ensure compliance with industry standards.

7. Document Maintenance Procedures

Documentation is an essential aspect of any maintenance strategy. Keeping detailed records of maintenance activities, configurations, and performance metrics allows for better decision-making and troubleshooting.

Action Steps:

Create a Maintenance Log: Document all maintenance activities, including software updates, hardware changes, and performance metrics.

Use Standard Operating Procedures (SOPs): Develop SOPs for routine tasks to ensure consistency and efficiency.

8. Plan for Future Upgrades

As technology continues to evolve, planning for future upgrades is essential to stay competitive. The IBM Power 10 servers are built for scalability, allowing organizations to expand their capabilities as needed.

Action Steps:

Evaluate Future Needs: Regularly assess your organization's growth and technology needs to determine when an upgrade may be necessary.

Explore Additional Features: Investigate the advanced features and capabilities of IBM Power 10 to leverage their full potential as your organization evolves.

Conclusion

Maintaining optimal performance for your IBM servers, particularly the Used IBM Power 10, requires a multifaceted approach that includes software updates, performance monitoring, regular backups, and physical inspections. By implementing these strategies, organizations can ensure their systems remain efficient, secure, and capable of handling the ever-increasing demands of modern workloads.

Effective server maintenance not only prolongs the life of your equipment but also enhances overall productivity and business continuity. As you focus on these strategies, remember that proactive maintenance is the key to leveraging the full power of your IBM infrastructure.

[semiconductorsandelectronics]

AI Vision Industry worth USD 43.02 billion in 2029

The report "AI Vision Market by Vision Software (API, SDK), Vision Platform, Behavioral Analysis, Optical Character Recognition, Spatial Analysis, Image Recognition, Heatmap Analysis, Machine Learning, Deep Learning, CNN, Generative AI – Global Forecast to 2029" The global AI vision market is expected to reach USD 43.02 billion in 2029 from USD 14. 85 billion in 2024, at a CAGR of 23.7% during the forecast period.

Al vision market is expanding during the forecasted period, driven by the increase in employment of machine learning and generative Al in multiple verticals. In healthcare, machine learning and generative Al provide the ability to improve the diagnostic accuracy of imaging and the use of data for patient monitoring. For In-store and e-commerce solutions, retailers have also adopted Al vision solutions for better inventory management and personnel shopper experience. In logistics and transport, Al Vision Solutions is adapted to focus on the real-time monitoring and automation of systems. Al Vision Solutions also helps monitor work sites and manage job sites in the construction sector. Thus, the rising demand for these technologies in various verticals is driving the Al vision market.

The image recognition segment is expected to have the largest market share in the forecast period.

The image recognition market is poised for the largest market share due to its ability to automate and streamline visual data analysis across industries. Technologies like Amazon Rekognition enhance efficiency in tasks such as security and retail management. Growing demand for AI-driven solutions and advancements in machine learning are driving this expansion. The technology’s versatility makes it highly valuable for diverse applications, fueling its widespread adoption and growth.

The machine learning segment is dominating in AI vision market.

The market for machine learning is projected to hold the dominant position within the Al vision space, as this type of technology allows systems to learn and improve in real-time from large amounts of visual data. The technology improves the accuracy of visual analysis, automates complex tasks, and removes humans from the process entirely (e.g, object detection and facial recognition). The recent improvements in deep learning and convolutional neural networks, along with machine learning's capability to expand the function of Al vision technology in general, are leading to substantially more industrial applications of Al vision technology in sectors including healthcare—manufacturing, retail, and security.

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US in the North America region to dominate the AI vision market during the forecast period.

The Al vision market in the US is positioned to be the leading part of North America due to significant federal investment, considerable technological innovation from the major tech companies, and the advancement of Al research and development. The establishment of several new Al Research Institutes and the commitment to funding for Al manufacturing all contribute to the US government's intent of advancing Al technology. The full spectrum of federal opportunities helps encourage collaboration among academia, Industry, and government and sustains tremendous growth in the US to facilitate growth for the Al vision market.

Key players

The AI vision market includes significant Tier I and II players like NVIDIA Corporation (US), Microsoft Corporation (US), Intel Corporation (US), Alphabet Inc. (US), Amazon.com, Inc. (US), IBM (US), Oracle (US), Cognex Corporation (US), Qualcomm Technologies, Inc. (US), STMicroelectronics (Switzerland) are some of the key players in the AI vision market.