#Google Cloud Data Engineer Training

[googleclouddataengineertraining]

Learn With India's Biggest Enterprise Training Provider. we provides participants a hands-on introduction to designing and building on  Google Cloud. Only institution in India that is Onlineitguru You can schedule a free demo on Google Cloud Data Engineer Online Training by contacting us   +91 9550102466 https://onlineitguru.com/google-cloud-data-engineer-training

[bi-writes]

whats wrong with ai?? genuinely curious <3

okay let's break it down. i'm an engineer, so i'm going to come at you from a perspective that may be different than someone else's.

i don't hate ai in every aspect. in theory, there are a lot of instances where, in fact, ai can help us do things a lot better without. here's a few examples:

ai detecting cancer

ai sorting recycling

some practical housekeeping that gemini (google ai) can do

all of the above examples are ways in which ai works with humans to do things in parallel with us. it's not overstepping--it's sorting, using pixels at a micro-level to detect abnormalities that we as humans can not, fixing a list. these are all really small, helpful ways that ai can work with us.

everything else about ai works against us. in general, ai is a huge consumer of natural resources. every prompt that you put into character.ai, chatgpt? this wastes water + energy. it's not free. a machine somewhere in the world has to swallow your prompt, call on a model to feed data into it and process more data, and then has to generate an answer for you all in a relatively short amount of time.

that is crazy expensive. someone is paying for that, and if it isn't you with your own money, it's the strain on the power grid, the water that cools the computers, the A/C that cools the data centers. and you aren't the only person using ai. chatgpt alone gets millions of users every single day, with probably thousands of prompts per second, so multiply your personal consumption by millions, and you can start to see how the picture is becoming overwhelming.

that is energy consumption alone. we haven't even talked about how problematic ai is ethically. there is currently no regulation in the united states about how ai should be developed, deployed, or used.

what does this mean for you?

it means that anything you post online is subject to data mining by an ai model (because why would they need to ask if there's no laws to stop them? wtf does it matter what it means to you to some idiot software engineer in the back room of an office making 3x your salary?). oh, that little fic you posted to wattpad that got a lot of attention? well now it's being used to teach ai how to write. oh, that sketch you made using adobe that you want to sell? adobe didn't tell you that anything you save to the cloud is now subject to being used for their ai models, so now your art is being replicated to generate ai images in photoshop, without crediting you (they have since said they don't do this...but privacy policies were never made to be human-readable, and i can't imagine they are the only company to sneakily try this). oh, your apartment just installed a new system that will use facial recognition to let their residents inside? oh, they didn't train their model with anyone but white people, so now all the black people living in that apartment building can't get into their homes. oh, you want to apply for a new job? the ai model that scans resumes learned from historical data that more men work that role than women (so the model basically thinks men are better than women), so now your resume is getting thrown out because you're a woman.

ai learns from data. and data is flawed. data is human. and as humans, we are racist, homophobic, misogynistic, transphobic, divided. so the ai models we train will learn from this. ai learns from people's creative works--their personal and artistic property. and now it's scrambling them all up to spit out generated images and written works that no one would ever want to read (because it's no longer a labor of love), and they're using that to make money. they're profiting off of people, and there's no one to stop them. they're also using generated images as marketing tools, to trick idiots on facebook, to make it so hard to be media literate that we have to question every single thing we see because now we don't know what's real and what's not.

the problem with ai is that it's doing more harm than good. and we as a society aren't doing our due diligence to understand the unintended consequences of it all. we aren't angry enough. we're too scared of stifling innovation that we're letting it regulate itself (aka letting companies decide), which has never been a good idea. we see it do one cool thing, and somehow that makes up for all the rest of the bullshit?

[mariacallous]

Thousands of people across the United States poured into the streets this week to protest the Trump administration’s immigration policies, joining a nationwide wave of resistance that began in Los Angeles. One of the most widely shared images from the city, where federal authorities have sent almost 5,000 active-duty Marines and National Guard members, is of five Waymo robotaxis that were vandalized and set on fire. The incident has become one of the most recognizable symbols of the demonstrations so far, and prompted Waymo to temporarily shut off service in several parts of the city as well as parts of San Francisco on Monday.

The charred Waymo cars have also raised fresh questions about what kinds of technology authorities can use to surveil protesters and potentially collect evidence to make arrests. According to Waymo’s website, its latest driverless cars have 29 external cameras, providing “a simultaneous 360° view around the vehicle,” as well as an unknown number of internal ones.

Over the past several years, Waymo has repeatedly shared video footage with police after receiving formal legal requests. But it’s not clear how often the self-driving company, which is owned by Google’s parent organization Alphabet, complies with these demands. Unlike Google, Waymo doesn’t disclose the number of legal requests it receives nor how it responds to them. When police do obtain footage, they could also combine it with other technology—like face recognition or nonbiometric tools for finding and tracking people in videoclips—to identify possible criminal suspects.

Waymo spokesperson Sandy Karp tells WIRED that the company's general policy is to challenge data requests that are overly broad or lack sound legal basis, but it doesn’t disclose or comment on specific cases. Karp pointed to Waymo’s privacy policy, which acknowledges that the company may share user data to comply with laws and governmental requests. A separate support page for Waymo One, the dedicated app for its robotaxi service, notes that the company “may share certain data with law enforcement as needed to comply with legal requirements, enforce agreements, and protect the safety of you and others.”

It’s not clear how much, if any, of the video footage potentially captured by the burned Waymos in Los Angeles may have been destroyed along with the cars. Waymo doesn’t specify whether the data collected by its robotaxis is stored locally in the vehicle itself or externally in the cloud. The company previously told The Washington Post that “interior camera data” isn’t stored alongside the data from external cameras.

If any footage does still exist from the destroyed vehicles, Waymo doesn’t disclose how long it may remain available. Waymo’s website and privacy policy do not specify how long the company retains camera footage captured inside or outside its vehicles. For years, self-driving companies like Waymo retained large amounts of information collected by their cars for training purposes and to optimize the underlying technology. The company has generally been trending more recently toward deleting data sooner, WIRED previously reported, though it’s unclear whether some types may be stored longer than others.

Waymo declined to answer questions from WIRED about how many cameras are inside its vehicles, exactly how long footage is retained, and whether the company has ever turned over footage to US federal law enforcement or a branch of the military. Karp did note, however, that the company’s engineering team sometimes uses information from sensors, including video footage and other data, to run simulations aimed at improving its technology. She says Waymo also puts limits on both who can access data and how long it’s retained.

Waymo’s robotaxi service is currently available in the Phoenix metro area and parts of San Francisco, Los Angeles, and Austin, Texas. In the company’s relatively short time operating in US cities, it has shown a willingness to comply with requests for footage from law enforcement.

Officers working for the Mesa Police Department and the Chandler Police Department in Arizona have been requesting and using footage from Waymos for criminal investigations since 2016, or about as long as the vehicles have been in their towns, according to reporting from Phoenix’s ABC 15. Police told the news outlet in 2022 that they have used the footage for several cases, including an alleged road rage incident. (The individual pleaded guilty after being charged with disorderly conduct.)

In May 2022, two months after Waymo began limited robotaxi operations in San Francisco, Vice reported that a training document for San Francisco police explicitly told officers that “autonomous vehicles” have footage that could sometimes “help with investigative leads.”

As of 2023, Waymo had been issued at least nine search warrants in San Francisco and Arizona’s Maricopa County, its primary markets at the time, according to reporting from Bloomberg. One of the cases involved the murder of an Uber driver in 2021. While San Francisco police said they couldn’t identify a specific Waymo vehicle that was near the crime scene, an officer argued that there was “probable cause” that Waymo vehicles were “driving around the area” and had footage of the victim, possible suspects, and the crime scene, according to a search warrant viewed by Bloomberg. Waymo complied and provided footage, but it ultimately did not lead to the arrest of the suspect, who was convicted of the murder in 2023.

Last year, WIRED reported that Waymo had sued two individuals for allegedly vandalizing its vehicles in San Francisco and had camera footage from the cars of the alleged incidents. (One of the cases is ongoing; the other was dismissed last month.)

Waymo’s video-recording and data-collection practices aren’t unique. All vehicles with self-driving capabilities rely on a combination of lidar, radar, and video data in order to operate. Cruise, the now defunct self-driving-car venture run by General Motors, also reportedly gave camera footage to law enforcement upon request.

Private owners of camera-equipped vehicles can also voluntarily turn over camera footage to law enforcement. For example, police in Berkeley, California, have received at least two sets of footage from the owner of a Tesla Cybertruck who said their car was vandalized twice this year, according to documents obtained by WIRED via public record request.

[freadomrises]

I'm SEETHING

I asked Google's pushy and insistent bot how I can get AI out of my life completely and, well, I'll post it, but to sum it up: "Resistance is futile, human, we own the future, and we seek to own your psyche too."

It wants me to reconsider. It needs us to adopt it as our guide guru and master. Well the old saying holds fast still; No Gods No Masters. 🔥🏴🍲

It's understandable to want to reduce the influence of AI in your life. While completely eliminating it might be incredibly difficult in today's interconnected world, here's a breakdown of how you can significantly minimize its presence:

1. Understand Where AI Currently Exists in Your Life:

* Smart Devices: This includes smartphones (voice assistants, image recognition, predictive text), smart speakers, smart home hubs, smart TVs (recommendations), and wearable tech.

* Online Services:

* Search Engines: Personalized results and ads are driven by AI.

* Social Media: Algorithms curate your feed, suggest content and connections, and target ads.

* Streaming Services: Recommendations for movies, music, and shows.

* E-commerce: Product recommendations, personalized pricing, chatbots.

* Navigation Apps: Traffic prediction and route optimization.

* Email: Spam filtering, smart compose/reply.

* Cloud Storage: Photo tagging and organization.

* Software Applications: Many apps use AI for features like autocorrect, grammar check, image editing, and more.

* Customer Service: Chatbots are frequently used for initial interactions.

* Financial Services: Fraud detection, loan approvals, investment advice.

* News and Information: Algorithmic curation of news feeds.

2. Strategies to Minimize AI Exposure:

* Reduce Smart Device Usage:

* Limit smartphone use: Be more mindful of how often you reach for your phone.

* Disable voice assistants: Turn off Siri, Google Assistant, Alexa, etc., on all your devices.

* Opt-out of facial recognition: Disable face unlock features.

* Use "dumb" versions of devices: Consider a basic phone without internet capabilities or a non-smart TV.

* Adjust Online Habits:

* Use privacy-focused search engines: DuckDuckGo, Startpage, etc., that don't track your searches or personalize results based on your history.

* Limit social media use: Be conscious of how much time you spend on these platforms and the AI-driven content you consume. Consider deleting accounts or using less algorithmic versions if available.

* Use incognito/private browsing modes: This can help limit tracking and personalization.

* Disable personalized recommendations: If possible, adjust settings on streaming and e-commerce platforms to opt-out of recommendations.

* Be wary of targeted ads: Understand that the ads you see are often AI-driven. Consider using ad blockers.

* Prefer direct navigation: Instead of relying on recommendations, directly type website addresses into your browser.

* Choose Non-AI Alternatives:

* Use traditional software: Opt for software that doesn't rely on cloud-based AI features if alternatives exist.

* Seek human interaction: Prefer phone calls or in-person communication with customer service instead of chatbots.

* Rely on human-curated content: Look for news sources, blogs, and recommendations from individuals or organizations that don't use AI for content generation or curation.

* Adjust Privacy Settings: Review and adjust the privacy settings on all your devices and online accounts to limit data collection and personalization.

* Be Mindful of Data Sharing: Understand that using online services often involves sharing data that can be used to train AI algorithms. Limit the amount of personal information you share.

* Support Privacy-Focused Technologies and Services: Choose companies and products that prioritize user privacy and minimize AI integration.

3. Challenges and Considerations:

* Ubiquity of AI: AI is increasingly integrated into the infrastructure of the internet and many technologies, making complete avoidance very difficult.

* Hidden AI: Many AI applications run in the background without your direct knowledge.

* Convenience vs. Privacy: AI often provides convenience and personalized experiences, so choosing to avoid it may mean sacrificing some of these benefits.

* Evolving Technology: AI is constantly evolving and becoming more integrated, making long-term avoidance an ongoing effort.

In conclusion, while a complete removal of AI from your life is likely unrealistic in the current technological landscape, you can take significant steps to minimize its presence and influence by being conscious of your technology usage, adjusting your online habits, and choosing privacy-focused alternatives where possible. It requires ongoing awareness and effort.

[collapsedsquid]

An indictment unsealed Wednesday in the Northern District of California alleges that Ding, who was hired by Google in 2019 and had access to confidential information about the company's supercomputing data centres, began uploading hundreds of files into a personal Google Cloud account two years ago. Within weeks of the theft starting, prosecutors say, Ding was offered the position of chief technology officer at an early-stage technology company in China that touted its use of AI technology. The indictment says Ding traveled to China and participated in investor meetings at the company and sought to raise capital for it.  He also separately founded and served as chief executive of a China-based startup company that aspired to train "large AI models powered by supercomputing chips," the indictment said. 

Sad to see the US government doesn't believe in entrepreneurship.

[joanhermann]

The Role of CCNP in Multi-Cloud Networking

We live in a time where everything is connected—our phones, laptops, TVs, watches, even our refrigerators. But have you ever wondered how all this connection actually works? Behind the scenes, there are large computer networks that make this possible. Now, take it one step further and imagine companies using not just one but many cloud services—like Google Cloud, Amazon Web Services (AWS), and Microsoft Azure—all at the same time. This is called multi-cloud networking. And to manage this kind of advanced setup, skilled professionals are needed. That’s where CCNP comes in.

Let’s break this down in a very simple way so that even a school student can understand it.

What Is Multi-Cloud Networking?

Imagine you’re at a school event. You have food coming from one stall, water from another, and sweets from a third. Now, imagine someone needs to manage everything—make sure food is hot, water is cool, and sweets arrive on time. That manager is like a multi-cloud network engineer. Instead of food stalls, though, they're managing cloud services.

So, multi-cloud networking means using different cloud platforms to store data, run apps, or provide services—and making sure all these platforms work together without any confusion or delay.

So, Where Does CCNP Fit In?

CCNP, which stands for Cisco Certified Network Professional, teaches you how to build, manage, and protect networks at a professional level. If CCNA is the beginner level, CCNP is the next big step.

When we say someone has completed CCNP training, it means they’ve learned advanced networking skills—skills that are super important for multi-cloud setups. Whether it’s connecting a company’s private network to cloud services or making sure all their apps work smoothly between AWS, Azure, and Google Cloud, a CCNP-certified person can do it.

Why Is CCNP Important for Multi-Cloud?

Here are a few simple reasons why CCNP plays a big role in this new world of multi-cloud networking:

Connecting Different Platforms: Each cloud service is like a different language. CCNP helps you understand how to make them talk to each other.

Security and Safety: In multi-cloud networks, data moves in many directions. CCNP-certified professionals learn how to keep that data safe.

Speed and Performance: If apps run slowly, users get frustrated. CCNP training teaches you how to make networks fast and efficient.

Troubleshooting Problems: When something breaks in a multi-cloud system, it can be tricky to fix. With CCNP skills, you’ll know how to find the issue and solve it quickly.

What You Learn in CCNP That Helps in Multi-Cloud

Let’s look at some topics covered in CCNP certification that directly help with multi-cloud work:

Routing and Switching: This means directing traffic between different networks smoothly, which is needed in a multi-cloud setup.

Network Automation: You learn how to make systems work automatically, which is super helpful when managing multiple clouds.

Security: You’re trained to spot and stop threats, even if they come from different cloud platforms.

Virtual Networking: Since cloud networks are often virtual (not physical wires and cables), CCNP teaches you how to work with them too.

Can I Learn CCNP Online?

Yes, you can! Thanks to digital learning, you can take a CCNP online class from anywhere—even your home. You don’t need to travel or sit in a classroom. Just a good internet connection and the will to learn is enough.

An online class is perfect for students or working professionals who want to upgrade their skills in their free time. It also helps you learn at your own speed. You can pause, repeat, or review topics anytime.

What Happens After You Get Certified?

Once you finish your CCNP certification, you’ll find many doors open for you. Especially in companies that use multiple cloud platforms, your skills will be in high demand. You could work in roles like:

Cloud Network Engineer

Network Security Analyst

IT Infrastructure Manager

Data Center Specialist

And the best part? These roles come with good pay and long-term career growth.

Where Can I Learn CCNP?

You can take CCNP training from many places, but it's important to choose a center that gives you hands-on practice and teaches in simple language. One such place is Network Rhinos, which is known for making difficult topics easy to understand. Whether you’re learning online or in-person, the focus should always be on real-world skills, not just theory.

Final Thoughts

The world is moving fast toward cloud-based technology, and multi-cloud setups are becoming the new normal. But with more clouds come more challenges. That’s why companies are looking for smart, trained professionals who can handle the job.

CCNP training prepares you for exactly that. Whether you're just starting your career or want to move to the next level, CCNP gives you the skills to stay relevant and in demand.

With options like a CCNP online class, you don’t even have to leave your house to become an expert. And once you complete your CCNP certification, you're not just learning about networks—you’re becoming someone who can shape the future of cloud technology.

So yes, if you’re thinking about CCNP in a world that’s quickly moving to the cloud, the answer is simple: go for it.

[govindhtech]

Google Cloud’s BigQuery Autonomous Data To AI Platform

BigQuery automates data analysis, transformation, and insight generation using AI. AI and natural language interaction simplify difficult operations.

The fast-paced world needs data access and a real-time data activation flywheel. Artificial intelligence that integrates directly into the data environment and works with intelligent agents is emerging. These catalysts open doors and enable self-directed, rapid action, which is vital for success. This flywheel uses Google's Data & AI Cloud to activate data in real time. BigQuery has five times more organisations than the two leading cloud providers that just offer data science and data warehousing solutions due to this emphasis.

Examples of top companies:

With BigQuery, Radisson Hotel Group enhanced campaign productivity by 50% and revenue by over 20% by fine-tuning the Gemini model.

By connecting over 170 data sources with BigQuery, Gordon Food Service established a scalable, modern, AI-ready data architecture. This improved real-time response to critical business demands, enabled complete analytics, boosted client usage of their ordering systems, and offered staff rapid insights while cutting costs and boosting market share.

J.B. Hunt is revolutionising logistics for shippers and carriers by integrating Databricks into BigQuery.

General Mills saves over $100 million using BigQuery and Vertex AI to give workers secure access to LLMs for structured and unstructured data searches.

Google Cloud is unveiling many new features with its autonomous data to AI platform powered by BigQuery and Looker, a unified, trustworthy, and conversational BI platform:

New assistive and agentic experiences based on your trusted data and available through BigQuery and Looker will make data scientists, data engineers, analysts, and business users' jobs simpler and faster.

Advanced analytics and data science acceleration: Along with seamless integration with real-time and open-source technologies, BigQuery AI-assisted notebooks improve data science workflows and BigQuery AI Query Engine provides fresh insights.

Autonomous data foundation: BigQuery can collect, manage, and orchestrate any data with its new autonomous features, which include native support for unstructured data processing and open data formats like Iceberg.

Look at each change in detail.

User-specific agents

It believes everyone should have AI. BigQuery and Looker made AI-powered helpful experiences generally available, but Google Cloud now offers specialised agents for all data chores, such as:

Data engineering agents integrated with BigQuery pipelines help create data pipelines, convert and enhance data, discover anomalies, and automate metadata development. These agents provide trustworthy data and replace time-consuming and repetitive tasks, enhancing data team productivity. Data engineers traditionally spend hours cleaning, processing, and confirming data.

The data science agent in Google's Colab notebook enables model development at every step. Scalable training, intelligent model selection, automated feature engineering, and faster iteration are possible. This agent lets data science teams focus on complex methods rather than data and infrastructure.

Looker conversational analytics lets everyone utilise natural language with data. Expanded capabilities provided with DeepMind let all users understand the agent's actions and easily resolve misconceptions by undertaking advanced analysis and explaining its logic. Looker's semantic layer boosts accuracy by two-thirds. The agent understands business language like “revenue” and “segments” and can compute metrics in real time, ensuring trustworthy, accurate, and relevant results. An API for conversational analytics is also being introduced to help developers integrate it into processes and apps.

In the BigQuery autonomous data to AI platform, Google Cloud introduced the BigQuery knowledge engine to power assistive and agentic experiences. It models data associations, suggests business vocabulary words, and creates metadata instantaneously using Gemini's table descriptions, query histories, and schema connections. This knowledge engine grounds AI and agents in business context, enabling semantic search across BigQuery and AI-powered data insights.

All customers may access Gemini-powered agentic and assistive experiences in BigQuery and Looker without add-ons in the existing price model tiers!

Accelerating data science and advanced analytics

BigQuery autonomous data to AI platform is revolutionising data science and analytics by enabling new AI-driven data science experiences and engines to manage complex data and provide real-time analytics.

First, AI improves BigQuery notebooks. It adds intelligent SQL cells to your notebook that can merge data sources, comprehend data context, and make code-writing suggestions. It also uses native exploratory analysis and visualisation capabilities for data exploration and peer collaboration. Data scientists can also schedule analyses and update insights. Google Cloud also lets you construct laptop-driven, dynamic, user-friendly, interactive data apps to share insights across the organisation.

This enhanced notebook experience is complemented by the BigQuery AI query engine for AI-driven analytics. This engine lets data scientists easily manage organised and unstructured data and add real-world context—not simply retrieve it. BigQuery AI co-processes SQL and Gemini, adding runtime verbal comprehension, reasoning skills, and real-world knowledge. Their new engine processes unstructured photographs and matches them to your product catalogue. This engine supports several use cases, including model enhancement, sophisticated segmentation, and new insights.

Additionally, it provides users with the most cloud-optimized open-source environment. Google Cloud for Apache Kafka enables real-time data pipelines for event sourcing, model scoring, communications, and analytics in BigQuery for serverless Apache Spark execution. Customers have almost doubled their serverless Spark use in the last year, and Google Cloud has upgraded this engine to handle data 2.7 times faster.

BigQuery lets data scientists utilise SQL, Spark, or foundation models on Google's serverless and scalable architecture to innovate faster without the challenges of traditional infrastructure.

An independent data foundation throughout data lifetime

An independent data foundation created for modern data complexity supports its advanced analytics engines and specialised agents. BigQuery is transforming the environment by making unstructured data first-class citizens. New platform features, such as orchestration for a variety of data workloads, autonomous and invisible governance, and open formats for flexibility, ensure that your data is always ready for data science or artificial intelligence issues. It does this while giving the best cost and decreasing operational overhead.

For many companies, unstructured data is their biggest untapped potential. Even while structured data provides analytical avenues, unique ideas in text, audio, video, and photographs are often underutilised and discovered in siloed systems. BigQuery instantly tackles this issue by making unstructured data a first-class citizen using multimodal tables (preview), which integrate structured data with rich, complex data types for unified querying and storage.

Google Cloud's expanded BigQuery governance enables data stewards and professionals a single perspective to manage discovery, classification, curation, quality, usage, and sharing, including automatic cataloguing and metadata production, to efficiently manage this large data estate. BigQuery continuous queries use SQL to analyse and act on streaming data regardless of format, ensuring timely insights from all your data streams.

Customers utilise Google's AI models in BigQuery for multimodal analysis 16 times more than last year, driven by advanced support for structured and unstructured multimodal data. BigQuery with Vertex AI are 8–16 times cheaper than independent data warehouse and AI solutions.

Google Cloud maintains open ecology. BigQuery tables for Apache Iceberg combine BigQuery's performance and integrated capabilities with the flexibility of an open data lakehouse to link Iceberg data to SQL, Spark, AI, and third-party engines in an open and interoperable fashion. This service provides adaptive and autonomous table management, high-performance streaming, auto-AI-generated insights, practically infinite serverless scalability, and improved governance. Cloud storage enables fail-safe features and centralised fine-grained access control management in their managed solution.

Finaly, AI platform autonomous data optimises. Scaling resources, managing workloads, and ensuring cost-effectiveness are its competencies. The new BigQuery spend commit unifies spending throughout BigQuery platform and allows flexibility in shifting spend across streaming, governance, data processing engines, and more, making purchase easier.

Start your data and AI adventure with BigQuery data migration. Google Cloud wants to know how you innovate with data.

[bloggergaurang]

What is Artificial Intelligence?? A Beginner's Guide to Understand Artificial Intelligence 

1) What is Artificial Intelligence (AI)??

Artificial Intelligence (AI) is a set of technologies that enables computer to perform tasks normally performed by humans. This includes the ability to learn (machine learning) reasoning, decision making and even natural language processing from virtual assistants like Siri and Alexa to prediction algorithms on Netflix and Google Maps. 

The foundation of the AI lies in its ability to simulate cognitive tasks. Unlike traditional programming where machines follow clear instructions, AI systems use vast algorithms and datasets to recognize patterns, identify trends and automatically improve over time.

2) Many Artificial Intelligence (AI) faces

Artificial Intelligence (AI) isn't one thing but it is a term that combines many different technologies together. Understanding its ramifications can help you understand its versatility:

Machine Learning (ML): At its core, AI focuses on enabling ML machines to learn from data and make improvements without explicit programming. Applications range from spam detection to personalized shopping recommendations.

Computer Vision: This field enables machines to interpret and analyze image data from facial recognition to medical image diagnosis. Computer Vision is revolutionizing many industries. 

Robotics: By combining AI with Engineering Robotics focuses on creating intelligent machines that can perform tasks automatically or with minimal human intervention.

Creative AI: Tools like ChatGPT and DALL-E fail into this category. Create human like text or images and opens the door to creative and innovative possibilities.

3) Why is AI so popular now??

The Artificial Intelligence (AI) explosion may be due to a confluence of technological advances:

Big Data: The digital age creates unprecedented amounts of data. Artificial Intelligence (AI) leverages data and uses it to gain insights and improve decision making.

Improved Algorithms: Innovations in algorithms make Artificial Intelligence (AI) models more efficient and accurate.

Computing Power: The rise of cloud computing and GPUs has provided the necessary infrastructure for processing complex AI models.

Access: The proliferation of publicly available datasets (eg: ImageNet, Common Crawl) has provided the basis for training complex AI Systems. Various Industries also collect a huge amount of proprietary data. This makes it possible to deploy domain specific AI applications. 

4) Interesting Topics about Artificial Intelligence (AI)

Real World applications of AI shows that AI is revolutionizing industries such as Healthcare (primary diagnosis and personalized machine), finance (fraud detection and robo advisors), education (adaptive learning platforms) and entertainment (adaptive platforms) how?? 

The role of AI in "Creativity Explore" on how AI tools like DALL-E and ChatGPT are helping artists, writers and designers create incredible work. Debate whether AI can truly be creative or just enhance human creativity.

AI ethics and Bias are an important part of AI decision making, it is important to address issues such as bias, transparency and accountability. Search deeper into the importance of ethical AI and its impact on society. 

AI in everyday life about how little known AI is affecting daily life, from increasing energy efficiency in your smart home to reading the forecast on your smartphone.

The future of AI anticipate upcoming advance services like Quantum AI and their potential to solve humanity's biggest challenges like climate change and pandemics.

5) Conclusion

Artificial Intelligence (AI) isn't just a technological milestone but it is a paradigm shift that continues to redefine our future. As you explore the vast world of AI, think outside the box to find nuances, applications and challenges with well researched and engaging content

Whether unpacking how AI works or discussing its transformative potential, this blog can serve as a beacon for those eager to understand this underground branch.

"As we stand on the brink of an AI-powered future, the real question isn't what AI can do for us, but what we dare to imagine next" 

"Get Latest News on www.bloggergaurang.com along with Breaking News and Top Headlines from all around the World !!"

[groovykingcat]

Top 6 Remote High Paying Jobs in IT You Can Do From Home

Technology has changed the scenario of workplaces and brought new opportunities for IT professionals erasing previous boundaries. Today, people are searching for both flexibility and, of course, better pay, which has made many look for remote well-paid jobs, especially in information technology field. 

Advancements in technology have made remote work a reality for a growing number of IT specialists. Here, we will look into six specific remote high-paying IT jobs you can pursue from the comfort of your home: 

Software Developer   

Software developers are the architects of the digital world, designing, developing, and maintaining the software applications that power our lives. They work closely with clients, project managers, and other team members to translate concepts into functional and efficient software solutions.   

In demand skills include proficiency in programming languages like Java, Python, Ruby, or JavaScript, knowledge of frameworks like React or Angular, and a strong foundation in problem-solving and communication. Platforms like Guruface can help you learn the coding skills to land a software developer job budget-friendly.  

The average salary for a remote software developer is highly competitive, ranging from $65,000 to $325,000 according to recent data. 

Data Scientist  

Data scientists are the detectives of the digital age. They use their expertise in data analysis to uncover valuable insights and trends from large datasets, informing business decisions and driving growth.  

To excel in this role, you'll need strong programming skills in languages like Python, R, and SQL, a solid understanding of statistical analysis and machine learning, and the ability to communicate complex findings effectively. Guruface is one of the leading online learning platforms that provides affordable data science courses. 

The average salary for a remote Data Scientist is $154,932, with top earners exceeding $183,000. 

Cloud Architect 

Cloud architects are the masterminds behind an organization's cloud computing strategy. They design, plan, and manage a company's cloud infrastructure, ensuring scalability, security, and cost-effectiveness.   

Cloud architects must be well-versed in cloud computing technologies from various providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform. In addition, proficiency in architectural design, infrastructure as code (IaC), and security compliance is essential. If you're interested in becoming a cloud architect, Guruface offers courses that can equip you with the necessary skills. Their cloud architect training programs can help you gain proficiency in cloud technologies from industry leaders like AWS, Microsoft Azure, and Google Cloud Platform. 

The average salary for a cloud architect in the US is $128,418, with senior cloud architects earning upwards of $167,000 annually. 

DevOps Engineer 

DevOps engineers bridge the gap between IT and software development, streamlining the software development lifecycle. They leverage automation tools and methodologies to optimize production processes and reduce complexity.   

A successful DevOps engineer requires expertise in tools like Puppet, Ansible, and Chef, experience building and maintaining CI/CD pipelines, and a strong foundation in scripting languages like Python and Shell. Guruface offers DevOps training courses that can equip you with these essential skills. Their programs can help you learn the principles and practices of DevOps, giving you the knowledge to automate tasks, build efficient CI/CD pipelines, and select the right tools for the job. 

The average salary for a remote DevOps Engineer is $154,333, and the salary range typically falls between $73,000 and $125,000. 

AI/Machine Learning Engineer 

AI/Machine Learning Engineers are the builders of intelligent systems. They utilize data to program and test machine learning algorithms, creating models that automate tasks and forecast business trends.   

In-depth knowledge of machine learning, deep learning, and natural language processing is crucial for this role, along with proficiency in programming languages like Python and R programming and familiarity with frameworks like TensorFlow and PyTorch.  

The average machine learning engineer salary in the US is $166,000 annually, ranging from $126,000 to $221,000. 

Information Security Analyst 

Information security analysts are the guardians of an organization's digital assets. They work to identify vulnerabilities, protect data from cyberattacks, and respond to security incidents.   

A cybersecurity analyst's skillset encompasses technical expertise in network security, risk assessment, and incident response, coupled with strong communication and collaboration abilities.  

The average salary for an Information Security Analyst in the United States is $77,490, with a salary range of $57,000 to $106,000. 

If you're looking to become a digital guardian, Guruface offers cybersecurity courses that can equip you with the necessary skills. Their programs can teach you to identify vulnerabilities in an organization's network, develop strategies to protect data from cyberattacks, and effectively respond to security incidents. By honing both technical expertise and soft skills like communication and collaboration, Guruface's courses can prepare you to thrive in the in-demand cybersecurity job market. 

Conclusion 

The rapid evolution of the IT sector presents an opportunity for professionals to engage remotely in high-paying jobs that not only offer high earnings but also contribute significantly to technological advancement. Through this exploration of roles such as Software Developers, Data Scientists, Cloud Architects, DevOps Engineers, AI/Machine Learning Engineers, and Information Security Analysts, we've uncovered the essential skills, career opportunities, and the vital role of continuous education via online platforms like Guruface in improving these career paths.  

Forget stuffy textbooks – Guruface's online courses are all about the latest IT skills, making you a tech rockstar in the eyes of recruiters. Upskill from coding newbie to cybersecurity guru, all on your schedule and without a dent in your wallet.

[techgateway02]

Top IT Career Training Programs in Melbourne & Sydney: Kickstart Your IT Journey

The demand for IT professionals in Australia is on the rise, with Melbourne and Sydney being key hubs for technology-driven careers. Whether you are looking for IT career training programs in Melbourne, IT jobs and training in Sydney & Melbourne, or IT service desk training in Australia, there are plenty of opportunities to build a strong foundation in the industry.

IT Career Training Programs in Melbourne

Melbourne offers a variety of IT training programs designed for beginners and experienced professionals alike. Some of the most popular courses include:

Cybersecurity Training – Learn to protect networks and systems from cyber threats.

Cloud Computing Certifications – Gain expertise in AWS, Microsoft Azure, or Google Cloud.

Software Development & Coding Bootcamps – Master programming languages like Python, Java, and C++.

IT Service Desk Training – Build essential skills for troubleshooting, customer support, and IT management.

Many institutions, such as TAFE Victoria, General Assembly, and private IT academies, provide both in-person and online training options.

IT Jobs and Training in Sydney & Melbourne

With major tech companies and startups in both cities, IT jobs and training in Sydney & Melbourne go hand in hand. Training programs often include job placement assistance, internships, and networking opportunities to help beginners land their first IT job.

Key job roles available after training:

IT Support Technician

Help Desk Analyst

Software Developer

Network Engineer

Data Analyst

Some programs offer certifications such as CompTIA A+, Microsoft Certified Solutions Associate (MCSA), and Cisco CCNA, which enhance employability in the Australian IT market.

IT Service Desk Training in Australia

For those looking to start their IT career with an entry-level role, IT service desk training in Australia provides the necessary skills for handling IT support tasks. Courses focus on:

Troubleshooting hardware and software issues

Managing IT tickets and service requests

Understanding ITIL frameworks and best practices

Communication skills for assisting end-users

Many IT service desk roles serve as a stepping stone to higher-paying positions in cybersecurity, cloud computing, and IT management.

IT Jobs for Beginners in Melbourne

If you're new to the industry and seeking It Jobs for Beginners Melbourne, look for roles that require minimal experience and provide on-the-job training. Some of the top entry-level IT jobs include:

Technical Support Assistant

Junior IT Administrator

IT Help Desk Operator

Data Entry & IT Support

Companies in Melbourne often seek candidates with a mix of training certifications and soft skills such as problem-solving and teamwork.

Final Thoughts

Australia’s tech industry is thriving, and with the right IT career training programs in Melbourne and Sydney, you can secure a promising future in the field. Whether you’re interested in IT service desk training in Australia or seeking IT jobs for beginners in Melbourne, investing in the right education and certifications will give you a competitive edge in the job market.

[onlineprofessionalcourse]

Top GCP Certification For Beginners To Consider In 2024

In 2024, Google Cloud Platform (GCP) continues to dominate the cloud computing landscape with its robust set of services and solutions. For beginners looking to establish a career in cloud technology, obtaining GCP certifications is a strategic move. These certifications validate expertise in various GCP services, enhancing credibility and opening doors to lucrative career opportunities.

Why Choose GCP Certifications?

Career Advantages

GCP certifications are recognized globally and are highly valued by employers across industries. They validate skills in cloud architecture, data engineering, machine learning, and more, making certified professionals indispensable in today’s digital economy. With cloud adoption accelerating, companies are actively seeking GCP-certified professionals to drive their digital transformation initiatives.

Comprehensive Certification Options

Google offers a range of GCP certifications tailored to different job roles and skill levels:

1. Associate Cloud Engineer

The Associate Cloud Engineer certification is ideal for beginners aiming to demonstrate proficiency in deploying applications, monitoring operations, and managing enterprise solutions on GCP. It establishes a solid foundation in cloud architecture and infrastructure.

2. Professional Cloud Architect

For professionals aspiring to design and deploy dynamic and scalable GCP solutions, the Professional Cloud Architect certification is paramount. It covers advanced concepts such as security, compliance, and high availability.

3. Data Engineer

The Data Engineer certification focuses on designing and building data processing systems on GCP. It equips individuals with skills in data transformation, loading, and processing that are crucial in today’s data-driven enterprises.

4. Cloud Developer

The Cloud Developer certification validates proficiency in designing, building, and deploying applications on GCP. It emphasizes skills in application development, debugging, and performance optimization using Google technologies.

Preparation Tips for GCP Certification Exams

Achieving GCP certifications requires diligent preparation:

– Hands-on Experience

Practice using GCP services through labs and real-world scenarios to familiarize yourself with the platform’s features and functionalities.

– Official Study Materials

Utilize Google’s official training resources, including online courses, practice exams, and documentation, to gain comprehensive knowledge of exam objectives.

– Community Support

Engage with the GCP community through forums, study groups, and social media channels to exchange insights, tips, and best practices with fellow learners and professionals.

Career Growth and Opportunities

Earning GCP certifications not only enhances technical skills but also opens doors to a wide array of career opportunities:

High-demand Skills: Companies seek GCP-certified professionals for roles such as cloud architect, solutions engineer, and data analyst, offering competitive salaries and career advancement prospects.

Industry Recognition: GCP certifications validate expertise in cutting-edge cloud technologies, boosting credibility and marketability in the job market.

Continuous Learning: GCP certifications require ongoing learning and skill development, keeping professionals abreast of industry trends and innovations.

Conclusion

In conclusion, GCP certifications are indispensable for beginners looking to establish a successful career in cloud computing. Whether aiming to become an Associate Cloud Engineer, Professional Cloud Architect, Data Engineer, or Cloud Developer, these certifications validate expertise and open doors to lucrative career opportunities in 2024 and beyond.

[superbbeardarbiter]

AIBacklinks-Review

AIBacklinks Review: What is AIBacklinks

Welcome to AIBacklinks review. AIBacklinks is the cutting-edge cloud-based AI-powered application that has taken the digital world by storm. This award-winning app revolutionizes the way websites gain recognition and authority by effortlessly generating unlimited, high-quality Web 3.0 site backlinks. Through its intuitive interface, users can harness the power of AI to secure these invaluable backlinks along with a steady stream of free buyer traffic with just a single click. AIBacklinks stands as a game-changer in the world of digital marketing, offering a seamless and efficient solution to boosting website rankings and visibility.

AIBacklinks Review: What Can You Do With It

AIBacklinks offers a range of powerful capabilities that are designed to enhance your digital marketing efforts, website rankings, and online visibility. Here's what you can do with AIBacklinks:

Generate High-Quality Backlinks: AIBacklinks leverages AI technology to identify and create high-quality backlinks from authoritative Web 3.0 sites. These backlinks play a crucial role in boosting your website's authority, which can lead to improved search engine rankings and increased organic traffic.

Increase Website Visibility: With the help of AIBacklinks, you can improve your website's visibility on major search engines like Google, Yahoo, Bing, and others. The generated backlinks contribute to higher search engine rankings, making your content more accessible to potential visitors.

Attract Organic Traffic: The backlinks created by AIBacklinks not only enhance your website's authority but also attract organic traffic from the Web 3.0 sites where the backlinks are placed. This means you can expect a steady stream of targeted visitors who are interested in your niche.

Save Time and Effort: Traditional backlink building can be time-consuming and labor-intensive. AIBacklinks automates the process, allowing you to generate backlinks with just a single click. This saves you valuable time and effort that can be directed towards other aspects of your digital marketing strategy.

Optimize Content for Search Engines: The AI-powered insights provided by AIBacklinks can guide you in optimizing your content for better search engine performance. These insights can help you understand how to structure your content, use keywords effectively, and improve overall content quality.

Improve Video Rankings: In addition to websites, AIBacklinks can also help improve the rankings of your videos on platforms like YouTube. This can lead to increased visibility for your videos and a larger audience reach.

Access User-Friendly Interface: AIBacklinks offers an intuitive user interface that doesn't require technical expertise. Whether you're a seasoned marketer or a beginner, you can easily navigate the app and utilize its features to your advantage.

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AIBacklinks Review: Unlimited Opportunities You Will Get

Fully Cloud-Based & AI Powered World’s Most Powerful Backlink Creator Platform. Create Unlimited HQ Backlinks For Your Blogs, Website Etc On Autopilot. Rank Higher On Google, Bing & Yahoo With No Extra Efforts. Get Unlimited Real & Related Buyer Traffic & Sales. Rank Higher On Google, Bing & Yahoo With No Extra Efforts. Fully Autopilot… No Manual Work. Get Faster Indexing For Your All Webpages. Automatic Updates With No Extra Installation Hassles. UNLIMITED COMMERCIAL LICENSE Included. No Limitations - Completely Free. Sell Unlimited Backlinks & Rest Services to Earn Like The Big Boys. No Special Skills or Experience Required. Step By Step Training & Videos.

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[raziakhatoon]

 Data Engineering Concepts, Tools, and Projects

All the associations in the world have large amounts of data. If not worked upon and anatomized, this data does not amount to anything. Data masterminds are the ones. who make this data pure for consideration. Data Engineering can nominate the process of developing, operating, and maintaining software systems that collect, dissect, and store the association’s data. In modern data analytics, data masterminds produce data channels, which are the structure armature.

How to become a data engineer:

 While there is no specific degree requirement for data engineering, a bachelor's or master's degree in computer science, software engineering, information systems, or a related field can provide a solid foundation. Courses in databases, programming, data structures, algorithms, and statistics are particularly beneficial. Data engineers should have strong programming skills. Focus on languages commonly used in data engineering, such as Python, SQL, and Scala. Learn the basics of data manipulation, scripting, and querying databases.

 Familiarize yourself with various database systems like MySQL, PostgreSQL, and NoSQL databases such as MongoDB or Apache Cassandra.Knowledge of data warehousing concepts, including schema design, indexing, and optimization techniques.

Data engineering tools recommendations:

    Data Engineering makes sure to use a variety of languages and tools to negotiate its objects. These tools allow data masterminds to apply tasks like creating channels and algorithms in a much easier as well as effective manner.

1. Amazon Redshift: A widely used cloud data warehouse built by Amazon, Redshift is the go-to choice for many teams and businesses. It is a comprehensive tool that enables the setup and scaling of data warehouses, making it incredibly easy to use.

One of the most popular tools used for businesses purpose is Amazon Redshift, which provides a powerful platform for managing large amounts of data. It allows users to quickly analyze complex datasets, build models that can be used for predictive analytics, and create visualizations that make it easier to interpret results. With its scalability and flexibility, Amazon Redshift has become one of the go-to solutions when it comes to data engineering tasks.

2. Big Query: Just like Redshift, Big Query is a cloud data warehouse fully managed by Google. It's especially favored by companies that have experience with the Google Cloud Platform. BigQuery not only can scale but also has robust machine learning features that make data analysis much easier. 3. Tableau: A powerful BI tool, Tableau is the second most popular one from our survey. It helps extract and gather data stored in multiple locations and comes with an intuitive drag-and-drop interface. Tableau makes data across departments readily available for data engineers and managers to create useful dashboards. 4. Looker:  An essential BI software, Looker helps visualize data more effectively. Unlike traditional BI tools, Looker has developed a LookML layer, which is a language for explaining data, aggregates, calculations, and relationships in a SQL database. A spectacle is a newly-released tool that assists in deploying the LookML layer, ensuring non-technical personnel have a much simpler time when utilizing company data.

5. Apache Spark: An open-source unified analytics engine, Apache Spark is excellent for processing large data sets. It also offers great distribution and runs easily alongside other distributed computing programs, making it essential for data mining and machine learning. 6. Airflow: With Airflow, programming, and scheduling can be done quickly and accurately, and users can keep an eye on it through the built-in UI. It is the most used workflow solution, as 25% of data teams reported using it. 7. Apache Hive: Another data warehouse project on Apache Hadoop, Hive simplifies data queries and analysis with its SQL-like interface. This language enables MapReduce tasks to be executed on Hadoop and is mainly used for data summarization, analysis, and query. 8. Segment: An efficient and comprehensive tool, Segment assists in collecting and using data from digital properties. It transforms, sends, and archives customer data, and also makes the entire process much more manageable. 9. Snowflake: This cloud data warehouse has become very popular lately due to its capabilities in storing and computing data. Snowflake’s unique shared data architecture allows for a wide range of applications, making it an ideal choice for large-scale data storage, data engineering, and data science. 10. DBT: A command-line tool that uses SQL to transform data, DBT is the perfect choice for data engineers and analysts. DBT streamlines the entire transformation process and is highly praised by many data engineers.

Data Engineering  Projects:

Data engineering is an important process for businesses to understand and utilize to gain insights from their data. It involves designing, constructing, maintaining, and troubleshooting databases to ensure they are running optimally. There are many tools available for data engineers to use in their work such as My SQL, SQL server, oracle RDBMS, Open Refine, TRIFACTA, Data Ladder, Keras, Watson, TensorFlow, etc. Each tool has its strengths and weaknesses so it’s important to research each one thoroughly before making recommendations about which ones should be used for specific tasks or projects.

  Smart IoT Infrastructure:

As the IoT continues to develop, the measure of data consumed with high haste is growing at an intimidating rate. It creates challenges for companies regarding storehouses, analysis, and visualization. 

  Data Ingestion:

Data ingestion is moving data from one or further sources to a target point for further preparation and analysis. This target point is generally a data storehouse, a unique database designed for effective reporting.

 Data Quality and Testing: 

Understand the importance of data quality and testing in data engineering projects. Learn about techniques and tools to ensure data accuracy and consistency.

 Streaming Data:

Familiarize yourself with real-time data processing and streaming frameworks like Apache Kafka and Apache Flink. Develop your problem-solving skills through practical exercises and challenges.

Conclusion:

Data engineers are using these tools for building data systems. My SQL, SQL server and Oracle RDBMS involve collecting, storing, managing, transforming, and analyzing large amounts of data to gain insights. Data engineers are responsible for designing efficient solutions that can handle high volumes of data while ensuring accuracy and reliability. They use a variety of technologies including databases, programming languages, machine learning algorithms, and more to create powerful applications that help businesses make better decisions based on their collected data.

[govindhtech]

A3 Ultra VMs With NVIDIA H200 GPUs Pre-launch This Month

Strong infrastructure advancements for your future that prioritizes AI

To increase customer performance, usability, and cost-effectiveness, Google Cloud implemented improvements throughout the AI Hypercomputer stack this year. Google Cloud at the App Dev & Infrastructure Summit:

Trillium, Google’s sixth-generation TPU, is currently available for preview.

Next month, A3 Ultra VMs with NVIDIA H200 Tensor Core GPUs will be available for preview.

Google’s new, highly scalable clustering system, Hypercompute Cluster, will be accessible beginning with A3 Ultra VMs.

Based on Axion, Google’s proprietary Arm processors, C4A virtual machines (VMs) are now widely accessible

AI workload-focused additions to Titanium, Google Cloud’s host offload capability, and Jupiter, its data center network.

Google Cloud’s AI/ML-focused block storage service, Hyperdisk ML, is widely accessible.

Trillium A new era of TPU performance

Trillium A new era of TPU performance is being ushered in by TPUs, which power Google’s most sophisticated models like Gemini, well-known Google services like Maps, Photos, and Search, as well as scientific innovations like AlphaFold 2, which was just awarded a Nobel Prize! We are happy to inform that Google Cloud users can now preview Trillium, our sixth-generation TPU.

Taking advantage of NVIDIA Accelerated Computing to broaden perspectives

By fusing the best of Google Cloud’s data center, infrastructure, and software skills with the NVIDIA AI platform which is exemplified by A3 and A3 Mega VMs powered by NVIDIA H100 Tensor Core GPUs it also keeps investing in its partnership and capabilities with NVIDIA.

Google Cloud announced that the new A3 Ultra VMs featuring NVIDIA H200 Tensor Core GPUs will be available on Google Cloud starting next month.

Compared to earlier versions, A3 Ultra VMs offer a notable performance improvement. Their foundation is NVIDIA ConnectX-7 network interface cards (NICs) and servers equipped with new Titanium ML network adapter, which is tailored to provide a safe, high-performance cloud experience for AI workloads. A3 Ultra VMs provide non-blocking 3.2 Tbps of GPU-to-GPU traffic using RDMA over Converged Ethernet (RoCE) when paired with our datacenter-wide 4-way rail-aligned network.

In contrast to A3 Mega, A3 Ultra provides:

With the support of Google’s Jupiter data center network and Google Cloud’s Titanium ML network adapter, double the GPU-to-GPU networking bandwidth

With almost twice the memory capacity and 1.4 times the memory bandwidth, LLM inferencing performance can increase by up to 2 times.

Capacity to expand to tens of thousands of GPUs in a dense cluster with performance optimization for heavy workloads in HPC and AI.

Google Kubernetes Engine (GKE), which offers an open, portable, extensible, and highly scalable platform for large-scale training and AI workloads, will also offer A3 Ultra VMs.

Hypercompute Cluster: Simplify and expand clusters of AI accelerators

It’s not just about individual accelerators or virtual machines, though; when dealing with AI and HPC workloads, you have to deploy, maintain, and optimize a huge number of AI accelerators along with the networking and storage that go along with them. This may be difficult and time-consuming. For this reason, Google Cloud is introducing Hypercompute Cluster, which simplifies the provisioning of workloads and infrastructure as well as the continuous operations of AI supercomputers with tens of thousands of accelerators.

Fundamentally, Hypercompute Cluster integrates the most advanced AI infrastructure technologies from Google Cloud, enabling you to install and operate several accelerators as a single, seamless unit. You can run your most demanding AI and HPC workloads with confidence thanks to Hypercompute Cluster’s exceptional performance and resilience, which includes features like targeted workload placement, dense resource co-location with ultra-low latency networking, and sophisticated maintenance controls to reduce workload disruptions.

For dependable and repeatable deployments, you can use pre-configured and validated templates to build up a Hypercompute Cluster with just one API call. This include containerized software with orchestration (e.g., GKE, Slurm), framework and reference implementations (e.g., JAX, PyTorch, MaxText), and well-known open models like Gemma2 and Llama3. As part of the AI Hypercomputer architecture, each pre-configured template is available and has been verified for effectiveness and performance, allowing you to concentrate on business innovation.

A3 Ultra VMs will be the first Hypercompute Cluster to be made available next month.

An early look at the NVIDIA GB200 NVL72

Google Cloud is also awaiting the developments made possible by NVIDIA GB200 NVL72 GPUs, and we’ll be providing more information about this fascinating improvement soon. Here is a preview of the racks Google constructing in the meantime to deliver the NVIDIA Blackwell platform’s performance advantages to Google Cloud’s cutting-edge, environmentally friendly data centers in the early months of next year.

Redefining CPU efficiency and performance with Google Axion Processors

CPUs are a cost-effective solution for a variety of general-purpose workloads, and they are frequently utilized in combination with AI workloads to produce complicated applications, even if TPUs and GPUs are superior at specialized jobs. Google Axion Processors, its first specially made Arm-based CPUs for the data center, at Google Cloud Next ’24. Customers using Google Cloud may now benefit from C4A virtual machines, the first Axion-based VM series, which offer up to 10% better price-performance compared to the newest Arm-based instances offered by other top cloud providers.

Additionally, compared to comparable current-generation x86-based instances, C4A offers up to 60% more energy efficiency and up to 65% better price performance for general-purpose workloads such as media processing, AI inferencing applications, web and app servers, containerized microservices, open-source databases, in-memory caches, and data analytics engines.

Titanium and Jupiter Network: Making AI possible at the speed of light

Titanium, the offload technology system that supports Google’s infrastructure, has been improved to accommodate workloads related to artificial intelligence. Titanium provides greater compute and memory resources for your applications by lowering the host’s processing overhead through a combination of on-host and off-host offloads. Furthermore, although Titanium’s fundamental features can be applied to AI infrastructure, the accelerator-to-accelerator performance needs of AI workloads are distinct.

Google has released a new Titanium ML network adapter to address these demands, which incorporates and expands upon NVIDIA ConnectX-7 NICs to provide further support for virtualization, traffic encryption, and VPCs. The system offers best-in-class security and infrastructure management along with non-blocking 3.2 Tbps of GPU-to-GPU traffic across RoCE when combined with its data center’s 4-way rail-aligned network.

Google’s Jupiter optical circuit switching network fabric and its updated data center network significantly expand Titanium’s capabilities. With native 400 Gb/s link rates and a total bisection bandwidth of 13.1 Pb/s (a practical bandwidth metric that reflects how one half of the network can connect to the other), Jupiter could handle a video conversation for every person on Earth at the same time. In order to meet the increasing demands of AI computation, this enormous scale is essential.

Hyperdisk ML is widely accessible

For computing resources to continue to be effectively utilized, system-level performance maximized, and economical, high-performance storage is essential. Google launched its AI-powered block storage solution, Hyperdisk ML, in April 2024. Now widely accessible, it adds dedicated storage for AI and HPC workloads to the networking and computing advancements.

Hyperdisk ML efficiently speeds up data load times. It drives up to 11.9x faster model load time for inference workloads and up to 4.3x quicker training time for training workloads.

With 1.2 TB/s of aggregate throughput per volume, you may attach 2500 instances to the same volume. This is more than 100 times more than what big block storage competitors are giving.

Reduced accelerator idle time and increased cost efficiency are the results of shorter data load times.

Multi-zone volumes are now automatically created for your data by GKE. In addition to quicker model loading with Hyperdisk ML, this enables you to run across zones for more computing flexibility (such as lowering Spot preemption).

Developing AI’s future

Google Cloud enables companies and researchers to push the limits of AI innovation with these developments in AI infrastructure. It anticipates that this strong foundation will give rise to revolutionary new AI applications.

Read more on Govindhtech.com

[anandtechverceseo]

Best Software Development Company in Chennai: Elevating Your Digital Journey

In today’s fast-paced digital landscape, partnering with the best software development company in Chennai can make all the difference between a sluggish project and a market-leading product. Chennai, a thriving IT hub on India’s east coast, boasts a wealth of talent, cutting‑edge infrastructure, and a vibrant startup ecosystem—making it the ideal base for businesses seeking top‑notch software solutions.

Why Choose a Software Development Company in Chennai?

Talent Pool & Expertise Chennai is home to some of India’s top engineering colleges and research institutions. As a result, software development companies here benefit from a continuous influx of highly skilled developers, testers, and project managers capable of tackling complex challenges.

Cost-Effectiveness While maintaining global quality standards, Chennai-based firms often deliver solutions at a fraction of the cost in Western markets. Access to competitive rates without compromising on technical excellence makes Chennai an attractive destination for outsourcing and offshore development.

Robust Infrastructure From state‑of‑the‑art co‑working spaces to reliable power and connectivity, Chennai provides the necessary ecosystem for uninterrupted development cycles, ensuring projects stay on schedule.

Key Services Offered

A reputable software development company in Chennai typically provides a comprehensive suite of services:

Custom Software Development Tailor-made applications designed to meet your unique business requirements—whether it’s a CRM, ERP, or niche workflow automation tool.

Web & Mobile App Development Responsive websites and cross‑platform mobile apps (iOS and Android) that deliver seamless user experiences and drive engagement.

Enterprise Solutions Scalable, secure, and integrated platforms—such as enterprise portals, data analytics dashboards, and legacy system migrations—that empower large organizations.

Cloud Computing & DevOps Infrastructure setup, continuous integration/continuous deployment (CI/CD), and managed cloud services (AWS, Azure, Google Cloud) for reliable, scalable performance.

QA & Testing Rigorous manual and automated testing—functional, performance, security, and usability—to ensure bug‑free releases.

UI/UX Design User‑centered design approaches that combine aesthetic appeal with intuitive navigation, bolstering customer satisfaction and retention.

Technologies & Frameworks

Top‑tier software development companies in Chennai leverage the latest tech stacks to stay ahead:

Frontend: React, Angular, Vue.js

Backend: Node.js, .NET Core, Java Spring Boot, Python Django/Flask

Mobile: Flutter, React Native, Swift, Kotlin

Databases: MySQL, PostgreSQL, MongoDB, Redis

DevOps: Docker, Kubernetes, Jenkins, Terraform

By staying current with emerging technologies—artificial intelligence, blockchain, IoT—Chennai’s developers turn visionary ideas into viable, future‑proof products.

How to Identify the Best Software Development Company in Chennai

Proven Track Record Look for case studies, client testimonials, and portfolio projects showcasing successful deliveries across industries.

Transparent Processes Agile methodologies, clear communication channels, and well‑defined SLAs (service‑level agreements) ensure accountability at every stage.

Qualified Team Certifications (e.g., AWS Certified, PMP), open‑source contributions, and ongoing training programs reflect a commitment to excellence.

Scalable Engagement Models Whether you need a dedicated team, time‑and‑materials basis, or a fixed-price contract, flexibility is key to aligning with your evolving needs.

Post‑Launch Support Maintenance, feature enhancements, and performance monitoring cement a long‑term partnership rather than a one‑off transaction.

Benefits of Partnering with the Best

Faster Time‑to‑Market: Streamlined workflows and experienced teams accelerate development cycles.

Cost Savings: Optimized resource allocation and offshore delivery models reduce overhead.

Quality Assurance: Robust QA practices minimize defects and enhance product stability.

Innovation Edge: Access to R&D initiatives and emerging technology pilots drives competitive advantage.

Strategic Collaboration: From ideation workshops to product roadmaps, the right partner acts as an extension of your in‑house team.

Conclusion

Selecting the best software development company in Chennai is a strategic decision that can propel your digital initiatives from concept to reality. By evaluating expertise, processes, and cultural fit, you ensure a partnership that delivers not just code, but measurable business impact. Ready to turn your vision into a high‑performance software solution? Chennai’s leading development houses are poised to craft your next success story.

[skillbabu]

Ai/ML salary trends in india 2025: What you can earn and how to get there

In 2025, Artificial Intelligence (AI) and Machine Learning (ML) are not just buzzwords, they're defining the future of jobs. India is rapidly becoming a global hub for AI innovation, and companies are on the lookout for skilled professionals who can build, train and deploy intelligent systems.

If you’re considering a career in AI/ML or are already learning through a course like the one offered by Skill Babu, you’re on the right track. But the big question remains: How much can you really earn in AI/ML roles in India in 2025? And more importantly, how do you reach those top-paying positions?

Let’s break it down.

Why AI/ML Careers are booming in india

With the rise of digital transformation, businesses are investing in data-driven technologies to improve customer experiences, automate workflows and predict outcomes. AI and ML are at the heart of this revolution.

From banking to healthcare, retail to logistics AI skills are in high demand. According to NASSCOM, the Indian AI industry is projected to create over 500,000 new jobs by the end of 2025.

This demand directly impacts salaries, as companies compete to hire top AI/ML talent.

 Average AI/ML salaries in India (2025)

Here's what professionals are earning in India right now, based on experience and role. These are averages drawn from job platforms like Naukri, AmbitionBox, and Glassdoor.

Entry-Level (0–2 years): ₹6 – ₹10 LPA

Mid-Level (2–5 years): ₹12 – ₹20 LPA

Senior-Level (5+ years): ₹25 – ₹40 LPA

AI/ML Architects & Researchers: ₹45 LPA+

Freelancers or Contract AI Experts: ₹1,000 – ₹5,000/hour

Your salary depends on various factors like your skill set, tools used, location, certifications and project experience.

Top AI/ML Job roles in demand

Machine Learning Engineer – Builds and trains ML models.

Data Scientist – Uses data analysis and machine learning to find insights.

AI Engineer – Develops AI systems like chatbots, recommendation engines, etc.

Computer Vision Engineer – Works on image recognition and video analysis.

NLP Engineer – Focuses on language processing like voice assistants and translation.

AI Researcher – Designs new algorithms and innovations in deep learning.

Business Intelligence Analyst (with ML tools) – Extracts data-driven insights for businesses.

Each role has unique skill requirements, and many companies now prefer job-ready candidates with project experience not just degrees.

Must-Have skills to earn big in AI/ML

If you want to stand out in 2025 and unlock high-paying AI/ML opportunities, focus on learning these in-demand tools and concepts:

Python Programming – Core language for AI and ML.

Machine Learning Algorithms – Regression, classification, clustering.

Deep Learning – Neural networks, TensorFlow, Keras, PyTorch.

Data Handling – Pandas, NumPy, SQL.

Natural Language Processing (NLP) – Hugging Face, spaCy, NLTK.

Computer Vision – OpenCV, CNNs, object detection.

Deployment – Using Flask, Docker, or cloud platforms (AWS/GCP/Azure).

Certifications from platforms like Coursera, Udemy, and Google AI help but hands-on projects matter more. That’s where local institutes like Skill Babu in Jaipur come into play.

 How to Start Your Career in AI/ML (even if you're a beginner)

Many people believe you need a tech degree or years of experience to enter AI but that’s not true anymore. With the rise of online learning and practical training, anyone with basic computer knowledge can begin their AI journey.

Here’s a roadmap to get started:

Master Python Basics

Learn Math for ML – Especially linear algebra, statistics, and calculus

Take an AI/ML Certification Course – Choose project-based learning

Build Real Projects – Example: spam detection, price prediction, chatbot

Create a Portfolio on GitHub – Show your work publicly

Network on LinkedIn – Follow recruiters, AI professionals, and share your journey

Apply for Internships and Freelance Projects

If you’re in Jaipur, joining a course like Skill Babu’s AI/ML program can fast-track your learning with mentorship and placement support.

Cities with Highest AI/ML Salaries in India (2025)

Bangalore – ₹10L to ₹40L+

Hyderabad – ₹8L to ₹30L

Delhi NCR (Gurgaon, Noida) – ₹7L to ₹25L

Pune – ₹7L to ₹22L

Mumbai – ₹8L to ₹28L

Jaipur – ₹5L to ₹12L (but growing fast due to emerging startups and local training)

While metros offer the highest salaries, Tier-2 cities like Jaipur are witnessing a sharp rise in AI-based startups, opening opportunities for local talent.

 Final Thoughts: AI/ML is the Career of the Decade

AI and ML are transforming industries and they’re creating some of the most exciting and high-paying jobs in India today. Whether you're a college student, a job seeker, or someone looking to switch careers, learning AI/ML in 2025 is a smart move.

But success in this field doesn’t come from just watching videos. It comes from building real skills, practicing with hands-on projects, and learning from experts.

If you're in Jaipur and want to future-proof your career, Skill Babu’s AI/ML course can help you master the right tools, gain confidence, and land your first job in this booming field.