Monday, 1 September 2025

China's 'Darwin Monkey' is the world's largest brain-inspired supercomputer

China's 'Darwin Monkey' is the world's largest brain-inspired supercomputer

 Researchers in China have introduced the world's largest computer chip, and you've probably never heard of it. Dubbed “Darwin Monkey” or “Wukong”, the system is modelled on the neural structure of the macaque brain and consists of more than 2 billion artificial neurones and over 100 billion synapses. Scientists say the machine could provide a critical platform for efforts to build what's known as artificial general intelligence (AGI) — an aspirational level of machine smarts which, like human intelligence, would be general in the sense that it could apply to a variety of tasks.



China's Darwin Monkey Supercomputer Mimics Brain Signals While Using Minimal Power

According to a report, the system architecture is built on spiking neural networks that closely mimic the way neurones are communicating in biological brains. And rather than handling continuous binary states, SNNs communicate bursts of electrical activity—spikes—which are fired only when sufficient input has been accepted. This architecture enables data to be processed in parallel and savings in energy. Its developers claim it draws just 2,000W from the wall, and that it is hanging off 960 Darwin III neuromorphic chips - each with millions of spiking neurones.

China has created a supercomputer called "Darwin Monkey" or "Wukong," which is the biggest brain-inspired computer in the world. This system has over 2 billion artificial neurons and more than 100 billion synapses, similar to the brain structure of a macaque monkey.

Scientists in China developed this supercomputer based on the brain-like structure of a monkey.

It is named Darwin Monkey or "Wukong" and has more than 2 billion artificial neurons and over 100 billion synapses, which makes it similar to the neural structure of a macaque monkey.

The researchers believe this system can help neuroscientists study the brain and also help move closer to creating artificial general intelligence (AGI).

AGI is an AI system that can think and reason like a human.

Unlike regular computers that use binary code and process data in a linear way, Darwin Monkey uses a different approach called spiking neural networks (SNNs).

These networks work like the way neurons in a mammal's brain send signals. Neurons send electrical signals in bursts, which is how information is passed around in the brain.

Artificial neurons in SNNs do the same thing: they send signals only when they get enough electrical input.

This is similar to how real neurons fire. Software-based neural networks use algorithms that try to copy the human brain, but SNNs are more like a real brain. This makes them more powerful than traditional computers because they can handle data at the same time.

SNNs might also use less energy.

After sending a signal, artificial neurons take a short break, which means they don't fire as often. This helps save power.

Darwin Monkey uses only 2,000 watts of power, which is about the same as a kettle or hairdryer.

It uses 960 Darwin III neuromorphic chips, each of which can support up to 2.35 million spiking neurons.

Before Darwin Monkey, the largest neuromorphic system was Intel's Hala Point, which had 1.15 billion artificial neurons and 128 billion artificial synapses across 140,544 processing cores.

Intel claims it can do 20 quadrillion operations per second, but comparing neuromorphic computers to regular supercomputers is tricky because they work differently.

The team behind Darwin Monkey, from Zhejiang University and Zhejiang Lab, a joint research institute between the Zhejiang government and Alibaba, said the system has already shown it can handle tasks like logical reasoning, content creation, and math problems using an AI model from a Chinese startup called DeepSeek.



They are also using the system to simulate the brains of animals with different levels of brain complexity, like zebrafish and mice, as part of their research into brain science.



Darwin Monkey was developed after the release of Darwin Mouse ("Mickey") in September 2020, which had 120 million artificial neurons, similar to a mouse's brain.

Monday, 18 August 2025

Sam Altman’s Brain Chip Venture Is Mulling Gene Therapy Approach

Sam Altman’s Brain Chip Venture Is Mulling Gene Therapy Approach

Altman said he wants to be able to think something and have ChatGPT respond to it. The company is looking at an approach involving gene therapy that would modify brain cells. In addition, an ultrasound device would be implanted in the head that could detect and modulate activity in the modified cells.

  • Merge Labs is exploring the idea of genetically altering brain cells to make better implants, using an approach involving gene therapy and an ultrasound device.
  • The company, which has drawn interest from Sam Altman and OpenAI, is still in early stages and could evolve significantly, according to people familiar with the plans.
  • Altman said he wants to be able to think something and have ChatGPT respond to it, and is co-founding Merge Labs, with much of the company's support coming from OpenAI's ventures team.

The brain chip company that has drawn interest from Sam Altman and his artificial intelligence business OpenAI is exploring the idea of genetically altering brain cells to make better implants.   The company, which has been appertained to as Merge Labs, is looking at an approach involving gene  remedy that would modify brain cells, according to people familiar with the plans who were n’t authorized to speak intimately on the matter. In addition, an ultrasound device would be implanted in the head that could  descry and modulate  exertion in the modified cells, these people said.   It’s one of a  sprinkle of ideas and technologies the company has been exploring, they said. The adventure is still in early stages and could evolve significantly. 



  “ We have n't done that deal yet, ” Altman told  intelligencers at a  regale Thursday in San Francisco,  pertaining to a question about a brain- computer interface adventure. “ I would like us to. ”   Altman said he wants to be  suitable to  suppose  commodity and have ChatGPT respond to it.   Merge Labs is Altman’s  rearmost  incursion into the brain- computer interface field. He's facing off against his longtime rival, Elon Musk, whose company Neuralink is  erecting brain implants with the short- term  thing of treating  complaint and the long- term ambition of  perfecting  mortal  capacities.   

OpenAI declined to  note.   Brain- computer interface companies aim to  make  bias that connect computers to  smarts and  compound peoples’ cognition. Implants are  presently enabling paralyzed cases to control electronics and helping people communicate who are  unfit to talk. Technology billionaires and investors are also auspicious that noninvasive  bias worn outside of the head could treat  internal health conditions.   

The Financial Times reported this week that Merge is aiming to raise$ 250 million at an$ 850 million valuation. important of that support will come from OpenAI’s  gambles  platoon, according to the report. Altman isco-founding the company but not  tête-à-tête investing in it, according to the Financial Times.   

Altman has also invested in Neuralink, Elon Musk’s brain implant  incipiency. Neuralink, along with several other companies, is developing chips that communicate with the brain using electrical signals, not ultrasound.   For times, experimenters have been studying how to genetically change cells to make them respond to ultrasound, a field called sonogenetics. The idea Merge is considering to combine ultrasound with gene  remedy could take times, some of the people said.   

Ultrasound has attracted significant attention  lately as a possible brain  remedy. Other companies are exploring the idea of using ultrasound transmitters outside the brain to massage brain towel, with the  thing of treating psychiatric conditions. That kind of technology has shown  pledge in  exploration studies.   Coinbaseco-founder Fred Ehrsam’s company Nudge, which is aiming to  make a helmet that beams low- intensity  concentrated ultrasound into the brain,  lately raised$ 100 million. LinkedInco-founder Reid Hoffman is leading a$ 12 million backing round in a  analogous company.  

Tuesday, 29 July 2025

Why Nvidia CEO Jensen Huang and Elon Musk want students to study physics instead of coding in the AI era

 

Nvidia CEO Jensen Huang says he’d study physics over coding if he were a student today, echoing Elon Musk’s advice to focus on real-world sciences for the AI-driven future.

In a world increasingly shaped by artificial intelligence and automation, some of the most influential tech leaders are urging a surprising pivot. Instead of doubling down on software and coding, Nvidia CEO Jensen Huang and Tesla CEO Elon Musk want today’s students to focus on the fundamentals—particularly physics and mathematics.

Jensen Huang: The case for physical sciences

During a recent event in Beijing, Nvidia’s Jensen Huang was asked what he would study if he were a 22-year-old graduate in 2025. His response caught many off guard. “I probably would have studied physical sciences,” Huang said, prioritizing physics over computer science. Despite building Nvidia into the world’s most valuable chipmaker, Huang believes that the next frontier in AI is not just software-driven but rooted in understanding the physical world.

Huang stressed that future AI systems—especially those operating in robotics and real-world environments—will require deep knowledge of physics. “The next wave requires us to understand friction, inertia, and cause and effect,” he noted, referring to what he calls “Physical AI.” As AI moves beyond perception and reasoning into real-world interaction, skills in physics, mechanics, and materials science will become increasingly valuable.


To that, the Nvidia CEO said: “For the young, 20-year-old Jensen, that’s graduated now, he probably would have chosen ... more of the physical sciences than the software sciences,” adding that he actually graduated two years early from college, at age 20.

Physical science, as opposed to life science, is a broad branch that focuses on the study of non-living systems, including physics, chemistry, astronomy and earth sciences.

Huang got his electrical engineering degree from Oregon State University in 1984 before earning his master’s degree in electrical engineering from Stanford University in 1992, according to his LinkedIn profile.

About a year later, in April 1993, Huang co-founded Nvidia with fellow engineers Chris Malachowsky and Curtis Priem over a meal at a Denny’s restaurant in San Jose, California. Under Huang’s leadership as CEO, the chipmaker has now become the world’s most valuable company.

Nvidia also became the world’s first company to hit a $4 trillion market cap last week.

Although Huang didn’t explain why he says he’d study the physical sciences if he were a student again today, the tech founder has been very bullish on “Physical AI” or what he calls the “next wave.”


Over the past decade and a half, the world has moved through multiple phases of artificial intelligence, he explained in April at The Hill & Valley Forum in Washington, D.C.


“Modern AI really came into consciousness about 12 to 14 years ago, when AlexNet came out and computer vision saw its big, giant breakthrough,” Huang said at the forum.


AlexNet was a computer model unveiled during a 2012 competition that demonstrated the ability of machines to recognize images using deep learning, helping spark the modern AI boom.


This first wave is called ‘Perception AI,’ Huang said.


Then, came the second wave called “Generative AI,” “which is where the AI model has learned how to understand the meaning of the information but [also] translate it” into different languages, images, code and more.

Elon Musk and the math-physics mantra

Elon Musk, known for companies like Tesla and SpaceX, has long championed physics as the foundation of all serious problem-solving. In response to a viral post by Telegram CEO Pavel Durov urging students to master mathematics, Musk simply added: “Physics (with math).” He has consistently said that understanding first principles—fundamental truths derived from physics—is key to building scalable innovation.

Musk’s endorsement aligns with his real-world projects. From rockets to autonomous cars, the challenges he tackles demand a mastery of physics far beyond software logic.

Why this shift matters

The advice from Huang and Musk marks a broader shift in thinking. While coding remains a critical skill, these leaders are advocating a return to the scientific roots that power real-world innovation. Physical AI and robotics are seen as the future of human-machine collaboration, and success in these fields depends less on writing code and more on understanding how the world works

Wednesday, 25 June 2025

OpenAI Takes on Google Docs and Microsoft Word with New ChatGPT Features

 OpenAI Takes on Google Docs and Microsoft Word with New ChatGPT Features

In a bold move, OpenAI is stepping into a new space – online document editing and collaboration – a field long dominated by giants like Google Docs and Microsoft Word for the web. With powerful new updates to ChatGPT, OpenAI is not just offering AI chat anymore; it’s aiming to become your go-to place for writing, editing, and sharing documents.

Let’s explore what OpenAI is doing, what features are coming, and how this might change the way we work online.


A New Direction for ChatGPT

ChatGPT is already one of the world’s most popular AI tools. Millions use it to ask questions, get help with writing, solve math problems, and even build websites. But now, OpenAI wants ChatGPT to be more than just a chatbot. The company is working on features that make ChatGPT behave more like a full office suite – like Google Docs or Microsoft Word Online.

According to recent reports, OpenAI is adding features to ChatGPT that will let users:

  • Write and edit documents with others in real-time
  • Chat inside the document about edits and suggestions
  • Organize files and folders
  • Collaborate on projects just like in Google Docs

These features could change how people write and work with documents, especially in business, education, and content creation.


The Rise of ChatGPT as a Productivity Tool

Earlier, people mostly used ChatGPT to generate content. But over time, more users – especially teams and businesses – wanted to use it for daily work. That includes drafting reports, summarizing meeting notes, editing emails, and much more.

OpenAI listened to these users and started improving ChatGPT for workplace use. Here are some examples of what’s already been done:

  • Record Mode: A feature that lets ChatGPT take notes from meeting recordings.
  • Connectors: Now, you can connect your Google Drive, Dropbox, OneDrive, or Box directly to ChatGPT and let it search or summarize documents.
  • Team & Enterprise Plans: OpenAI launched special paid plans for teams that offer better privacy, data security, and group work options.

But the latest updates go even further. Now, the company is building full document editing and collaboration tools right into ChatGPT. That’s where things start to look like Google Docs and Microsoft Word.


The “Canvas” Feature: AI + Editing

One of the most important features in this direction is something called Canvas. This tool was introduced in late 2024 and is slowly becoming more powerful.

Canvas is a workspace inside ChatGPT where you can:

  • Write and edit long documents
  • See the AI’s suggestions side-by-side
  • Accept or reject changes
  • Collaborate with others in real-time

It’s like Google Docs, but with a powerful AI editor helping you along the way. You can work with others, edit together, and even hold a chat-based discussion inside the same page. For writers, marketers, students, or office workers, this could be a major upgrade.


Why OpenAI Is Doing This

So why is OpenAI moving into document collaboration? There are a few big reasons:

1. Huge Market Opportunity

Google Docs and Microsoft Word Online are used by hundreds of millions of people every day. These tools are essential for offices, schools, and freelancers. If OpenAI can offer a smarter, AI-powered version of these tools, it could attract many users.

2. Business Focus

OpenAI is making a strong push into business services. In 2024, it earned over $600 million in business subscriptions, and by 2030, it could be earning over $15 billion. Adding document tools will make ChatGPT more useful to teams and companies.

3. Challenge to Microsoft and Google

Even though Microsoft is a major investor in OpenAI, the two companies may become rivals in this space. Microsoft already uses GPT inside Word and Excel (as part of its Copilot system), but now OpenAI is building a competing product. Google, too, has its own AI features in Docs. OpenAI is stepping into their territory.


What Makes ChatGPT Different?

You might wonder: why use ChatGPT for documents when Google Docs and Microsoft Word already work so well?

Here are some ways ChatGPT’s system could stand out:

  • AI First: Everything in the new ChatGPT tools is built around AI. That means automatic writing help, grammar fixes, summaries, tone changes, and more.
  • Smart Suggestions: Instead of just spell check, ChatGPT can suggest whole rewrites, explain grammar, or adjust the tone for a formal email.
  • Unified Chat and Work: While Google Docs and Word let you comment or suggest edits, ChatGPT gives you a real-time chatbot inside the document. You can ask questions like, “Can you make this sound more professional?” and get an instant reply.
  • Connected Data: Since you can link your cloud drives (Google Drive, Dropbox, etc.), ChatGPT can read, search, and summarize your files without you needing to open them.



How Will This Affect Google and Microsoft?

This is a tricky situation. Microsoft is a key partner and investor in OpenAI. But now OpenAI is moving into Microsoft’s business space — document editing. Microsoft already offers Copilot inside Word, which uses OpenAI’s models. So in a way, Microsoft and OpenAI are both competing and cooperating.

For Google, this is a more direct challenge. Google has been adding AI features to Docs and Sheets too, but many users say ChatGPT’s writing abilities are still better. If OpenAI can create a tool that’s as easy to use as Google Docs but smarter, it could pull users away.


Who Should Be Excited?

These new features will help many people:

Teachers and Students

Imagine writing your assignment with AI feedback built in. Or having a study partner that helps you explain topics, corrects grammar, and checks for plagiarism.

Office Workers

Instead of switching between email, Docs, and chats, now everything can happen in one place – writing reports, discussing changes, and even summarizing meetings.

 Content Creators and Writers

Writers can use AI to generate content ideas, improve style, and even check SEO — all while writing in a shared document with clients or editors.


What’s Next?

While some of these features are already available to ChatGPT Plus, Team, and Enterprise users, more updates are coming soon. OpenAI has not yet shared exact dates for a full release, but previews show a clear direction: an AI-powered workspace where writing, chatting, and collaborating happen together.


Final Thoughts

The future of work is changing. With ChatGPT becoming more than just a chatbot — now a full document editor, writing assistant, and collaboration tool — we are entering a new era.

Google Docs and Microsoft Word will always have their place. But OpenAI is creating something smarter, faster, and more integrated. If these features continue to improve, ChatGPT could soon become your go-to tool for everything from writing a blog post to working on a group project.

So next time you open ChatGPT, don’t just ask it a question. Try writing something with it. The future of documents might be right in front of you.

 

Monday, 16 June 2025

Google & U.S. Experts Collaborate on AI Hurricane Forecasts

 Google & U.S. Experts Collaborate on AI Hurricane Forecasts

1. Google’s AI Cyclone Model Goes Live

Google DeepMind and Google Research launched Weather Lab, a publicly accessible site showcasing their experimental AI models for predicting tropical cyclones—or hurricanes—up to 15 days in advance, producing 50 forecast scenarios per storm. 

2. Integration with U.S. National Hurricane Center (NHC)

The NHC will begin experimentally using Google’s AI-generated forecasts alongside traditional models. This marks the first operational collaboration of its kind. 



3. Enhanced Accuracy & Speed

The system’s 5‑day track forecasts are on average about 140 km closer to the actual storm paths compared to ECMWF’s ENS model—roughly equivalent to 1.5 days of additional lead time. 

It also predicts storm intensity and size more accurately than NOAA's HAFS model. 

Impressively, the AI model can generate 15-day forecasts in about a minute, far faster than conventional physics-based models. 

4. Augmenting, Not Replacing, Traditional Forecasting

Google stresses the model is meant to complement—not replace—traditional weather forecasting methods. It remains an experimental tool, and official weather warnings will still originate from trusted public agencies .

Human forecasters at the NHC will review and combine AI forecasts with physics-based models and their own expertise.

5. Global Collaboration & Research Validation

Google is working with the NHC, Colorado State University, the UK Met Office, University of Tokyo, and Japan Weathernews, among others, to refine and validate its models. 

The Weather Lab platform includes historical backtesting of AI forecasts, enabling experts to assess performance across multiple past storms.  

 Why This Matters

Earlier, more accurate warnings can save lives and reduce property damage.

The blend of AI speed and accuracy with human judgment represents a significant leap forward in forecasting capability.

As hurricane seasons intensify, improvements in predictive power are critical for emergency preparedness and climate adaptation efforts.

Let me know if you'd like a deeper dive into how the AI model works—its architecture, training data, or integration steps with operational forecasting!

🇮🇳 India Has Nearly 17 Million Developers

 🇮🇳 India Has Nearly 17 Million Developers

Anshul Ramachandran, from AI‑coding platform Windsurf (formerly Codeium), highlighted that India is now home to nearly 17 million software developers, second only to the U.S. 

lennysnewsletter.com

👥 AI Won’t Replace Developers — Just Help Them

Ramachandran argues that warnings about AI displacing developers are often exaggerated — sometimes “a very good excuse” for layoffs, or a way for AI companies to market their tools 

m.economictimes.com

. Instead, he sees AI as a productivity booster, not a job eliminator.

🌟 India: A Core Market for AI Tool Adoption

Windsurf values India as its second-largest market after the U.S. and is actively expanding teams and considering building GPU clusters there. He praised Indian developers and IT firms for being early and enthusiastic adopters of AI 

💡 Tactics Behind AI Narratives

According to Ramachandran, some AI company leaders amplify fears of AI replacing human coders to drive model sales. He suggests the narrative often serves business motives rather than reflecting reality 

🎯 Why It Matters

Massive talent pool: With ~17 million coders, India’s developer ecosystem is a fertile ground for generative AI tools.


Boost, not replace: AI is positioned as a “co-pilot” — enhancing coding efficiency without removing the human element.

Industry acceleration: High AI adoption rates in India could accelerate global standards in software engineering.


🔭 In Perspective

In the broader AI discourse:


The discourse on AI “replacement” often serves seller aims more than reflecting actual trends.


Instead, expect AI-assisted workflows to dominate — helping developers write, debug, and deploy faster.


India’s sheer developer numbers make it a key battleground for adoption and innovation.


Want to explore more? I can share insights from Wind­s­urf’s CEO Varun Mohan on how AI is reshaping developer roles and startup dynamics, including his vision of “vibe coding” and building lean, agile teams.

Big Tech on a Quest for the Ideal AI Device

 Big Tech on a Quest for the Ideal AI Device

In the past few years, artificial intelligence (AI) has taken huge steps forward. From smart chatbots that write stories to AI tools that create music and art, technology is moving fast. But now, the biggest tech companies in the world—like Apple, Google, Meta, and Amazon—are racing to do something even bigger. They want to create a completely new kind of device: an AI device that is smarter, more helpful, and more natural to use than anything we’ve had before.

This isn’t just about making a better smartphone or a faster computer. It’s about inventing something totally different—a smart companion that’s always with you, understands your needs, and helps you without needing to be touched or typed into.

Let’s explore what this new AI device could look like, why it matters, and who’s leading the race.

What is an AI Device?

An AI device is not just a phone or a computer with AI features. It’s a new kind of product designed from the ground up to work with artificial intelligence. Imagine a small gadget—maybe something you wear on your shirt, glasses you put on your face, or a pocket-sized assistant—that’s always listening, learning, and helping you in real time.



This device wouldn’t have to be touched or swiped like a phone. You could talk to it, ask it questions, or even let it observe your surroundings to help with tasks. It might remind you of meetings, explain something you're looking at, help you shop, or translate a foreign language—all without using a screen.

This is what tech companies are trying to build: a new companion powered by AI.

Why is Everyone Racing to Build It?

The world’s biggest tech companies believe the future of technology will be centered around AI-first experiences. This means that instead of using apps and searching for things manually, your AI device will understand what you need and do it for you—before you even ask.

Think about how smart assistants like Siri, Alexa, or Google Assistant work today. Now imagine something 100 times smarter, more personal, and more helpful, always with you, and always improving.

If a company can create this perfect AI device, they could become the leader of the next big tech era—just like Apple did with the iPhone in 2007.

What Features Will the Ideal AI Device Have?

The perfect AI device will likely include:

  • Voice and Vision: It will use microphones and cameras to understand your voice and surroundings.
  • Context Awareness: It will know where you are, what you’re doing, and adjust its help accordingly.
  • Real-time Intelligence: It will answer questions, plan schedules, control smart devices, and more—instantly.
  • Privacy and Security: It will protect your personal data and use secure AI processing.
  • No Screen (or a Minimal One): Some versions may avoid screens completely, offering distraction-free interaction.
  • Battery Efficient: It must work all day without needing frequent charging.


In short, it should be like having a smart assistant in your pocket—one that’s quiet, helpful, and always alert.


Who is Building These Devices?

Apple

Apple is working on adding more powerful AI features to the iPhone, Mac, and even future wearable products. Rumors suggest Apple may be developing smart glasses with built-in AI and on-device AI chips that work without the internet. Apple’s strength is in combining beautiful design with strong privacy protection, which could help them build a trustworthy AI gadget.

Google

Google has already built strong AI tools with products like Gemini (its version of ChatGPT). It is now putting these tools into Android phones, smart speakers, and even exploring AI-powered glasses. In the future, Google may release a wearable device that helps you see information in real time, right in front of your eyes.

Meta (formerly Facebook)

Meta is focusing on AI smart glasses. In partnership with Ray-Ban, Meta has launched glasses that let users take pictures, listen to music, and even talk to an AI assistant. In the future, these glasses could become more advanced, allowing users to see useful information, get directions, and even recognize people or objects just by looking.

Amazon

Amazon is updating Alexa, its voice assistant, with more advanced AI. While Alexa is mostly used on home speakers today, Amazon may build a portable AI device for everyday use. This could include voice-first gadgets that help users manage their homes, calendars, and shopping needs on the go.

OpenAI + Jony Ive + SoftBank

Perhaps the most exciting project is a new AI device being developed by OpenAI (the creators of ChatGPT), Jony Ive (the legendary Apple designer), and SoftBank (a giant investor). This team is trying to build a completely new type of AI device—not a phone, not a laptop, but something never seen before. The goal is to create a device that people feel naturally connected to, one that uses AI to assist in a more human-like way.

Startups: Humane and Rabbit

Two smaller companies are already testing the waters:

Humane has launched an AI Pin, a small device you wear on your clothes. It listens to your voice and can even project information onto your hand using a tiny laser.

Rabbit has created a gadget called the R1, which can take your voice commands and carry out tasks like booking a ride, ordering food, or sending messages—without needing apps.

These devices are still early in development, but they show that the future is not far away.

Why Not Just Use a Smartphone?

Smartphones are great, but they are designed mainly for touch and screens. AI devices are being built for something different: natural, invisible assistance. They aim to reduce distraction, work faster, and provide help without requiring you to open an app or scroll.

The goal is to make technology feel more human and less technical—something that listens, watches, and responds without you needing to lift a finger.

What Are the Challenges?

Building the perfect AI device isn’t easy. Companies face some big problems:

  • Privacy: People don’t want to be spied on. Always-listening devices must be secure and respectful.
  • Battery Life: AI uses a lot of power. These devices must last a full day or more.
  • Usefulness: They must do things that phones can’t—otherwise, why switch?
  • Cost: If it’s too expensive, regular users may not buy it.
  • Trust: People need to trust the AI to make decisions or take actions for them.
  • Solving these problems will be key to success.
  • The Future: A World with Smart Companions

Within the next few years, we may all have a personal AI assistant with us—guiding us, organizing our lives, and helping us interact with the world.

The idea may sound like science fiction, but so did smartphones just 20 years ago. Now, they’re everywhere.

As AI continues to grow, the devices we use to access it will become more important. Whether it’s glasses that see and explain, pins that listen and respond, or totally new inventions, the AI device revolution is coming—and Big Tech doesn’t want to be left behind.

Wednesday, 4 June 2025

The AI Monopoly: How Big Tech Controls Data and Innovation

The AI Monopoly: How Big Tech Controls Data and Innovation

Artificial Intelligence (AI) is changing our lives every day. From how we shop to how we learn, get healthcare, and even how we are entertained, AI is everywhere. But behind this exciting future lies a serious concern — who controls AI and its data?

Right now, a few big tech companies like Google, Amazon, Microsoft, Meta (Facebook), and OpenAI control most of the important data that AI systems need. These companies are not just leading in AI technology; they are also building barriers that make it hard for others to catch up. This situation is called a monopoly, and it has major consequences for the future of technology, innovation, fairness, and privacy.




Why Data is So Important for AI

AI systems cannot work without data. Data is the fuel that powers AI. For example:

  • To train a chatbot like ChatGPT, millions or even billions of text samples are needed.

  • To create a face recognition system, thousands of images of faces must be provided.

  • For voice assistants, thousands of hours of recorded speech are needed.

The more data an AI model has, the smarter and more accurate it becomes. But not just any data — the data must be high-quality, diverse, and rich in context.

Big tech companies have an advantage because they already have access to massive amounts of user data. This is called proprietary data, which means it's exclusive and not publicly available. This makes it hard for smaller companies or startups to compete because they don't have the same level of data.


How Big Tech Gets and Uses Data

Big tech companies collect data in many ways:

  • Google collects data from searches, YouTube views, Google Maps, Gmail, and more.

  • Amazon collects data from shopping habits, browsing, product reviews, and more.

  • Facebook (Meta) collects data from posts, messages, likes, and even Instagram and WhatsApp.

  • Microsoft partners with healthcare, education, and government institutions to get sensitive and valuable data.

They then use this data to improve their AI systems. For example:

  • Google improves search results and video recommendations.

  • Amazon improves product suggestions and delivery systems.

  • Facebook uses AI to decide what content to show you.

These companies also combine data from their different services. For example, your YouTube activity can affect your Google Ads. This creates a loop — more user activity means more data, which means better AI, which attracts more users.


How Big Tech Blocks Competition

Big Tech does not just collect data — it also uses clever strategies to stay ahead and prevent others from catching up.

1. Exclusive Partnerships

They sign special deals with hospitals, universities, or governments. For example, Microsoft might work with a hospital to access medical records for AI research. These deals mean that no one else can access that same data.

2. Closed Ecosystems

Google, Facebook, and others keep their platforms tightly locked. You can use their services, but you don’t get access to their data. This prevents smaller companies or researchers from using that information for building their own AI.

3. Acquisitions

When a smaller company with valuable data or technology becomes successful, Big Tech often buys it out. Facebook bought Instagram and WhatsApp, not just for the apps, but also for the user data. Google bought Fitbit for the health and fitness data.

These moves make it harder for new companies to grow. Without data and access to users, they cannot build powerful AI tools.


Why This Monopoly is a Problem

When just a few companies control AI, there are serious problems:

1. Less Innovation

Small companies, startups, and independent researchers have a hard time entering the field. They don't have access to the kind of data needed to build strong AI. This means less competition, and slower progress in solving big world problems like climate change, healthcare, or poverty.

2. Biased AI Systems

AI is trained on the data it receives. If the data is not diverse, the AI will be biased. For example, many facial recognition systems fail to accurately identify people with darker skin tones because they were trained on mostly white faces. This kind of bias can lead to unfair results in jobs, justice, and policing.

3. Privacy Concerns

Companies like Google and Facebook collect a lot of personal data, sometimes without fully informing users. This data is used not just to improve services but also for advertising and profit. The Cambridge Analytica scandal is one example of how this data can be misused.

4. Limited Consumer Choice

When only a few companies control everything, consumers have fewer options. Prices can go up, features may be limited, and users have to accept terms they don’t fully understand.


The Need for Change

Right now, governments and global institutions are not doing enough to break this monopoly. Laws like Europe’s General Data Protection Regulation (GDPR) protect user privacy, but they don’t address the unfair power Big Tech holds due to exclusive data control.

We need to act quickly and smartly.

Solutions Include:

  • Open Data Projects: Initiatives like Common Crawl or Hugging Face collect and share large amounts of data freely. Governments and donors should support such projects to help smaller companies.

  • Public Data for Public Use: Governments can make anonymized data from public services (like hospitals or schools) available to approved researchers or companies. This would help create AI for social good.

  • Stronger Regulations: New laws should stop companies from making exclusive data deals that block others. Regulators should also monitor mergers and data acquisitions more closely.

  • Better Transparency: Companies should clearly explain how they collect and use data. Users should have more control over their information.

  • Ethical AI Development: AI models should be tested for fairness and bias. Companies must take responsibility if their AI systems cause harm.


The Way Forward

We are at a critical moment in the history of AI. If we allow a few companies to control all the data and tools, the future of AI will be designed to serve only their interests — mainly profit. But if we act wisely, we can build an AI future that is fair, ethical, innovative, and useful for everyone.

  • Governments, researchers, and companies must work together.

  • Open data and ethical AI must be supported with funding and policy.

  • People must demand transparency and privacy rights.


Conclusion

Big Tech’s control over data is shaping the future of AI. While these companies have built impressive tools, their monopoly over data is slowing down innovation, blocking fair competition, and raising major ethical concerns. But it doesn’t have to stay this way.

By promoting open data, enforcing new rules, and supporting fair access, we can break the AI monopoly and build a future where AI works for everyone — not just for the biggest companies.

The time to act is now. Together, we can create a more open, fair, and human-centered AI future.

Big Tech’s AI Endgame Is Coming Into Focus

 Big Tech’s AI Endgame Is Coming Into Focus



How Big Companies Are Racing to Build the Future of AI

In recent years, artificial intelligence (AI) has grown very quickly. Companies like Google, Apple, Microsoft, Meta (Facebook), Amazon, and OpenAI are investing billions of dollars to make smarter and more useful AI tools. These companies believe that AI will change the way we live, work, and interact with technology.

They are now focusing on something called an "everything app" — a super-smart AI assistant that can help you with many tasks, all in one place. This article explains what these everything apps are, why Big Tech wants to create them, how they work, and what problems they might bring.

What is an Everything App?

An everything app is a single digital assistant powered by AI that can do many things for you. Instead of using different apps for email, shopping, chatting, booking hotels, or writing documents, you would use just one AI assistant that can do all of those tasks.

Imagine having one smart helper on your phone or computer that understands what you want, answers your questions, writes messages for you, organizes your day, helps with your shopping, gives travel ideas, and much more.

This AI assistant doesn’t just give answers — it understands your needs and works like a partner. You don’t need to tell it every little detail. It learns your preferences over time and does things for you before you even ask.

How Big Tech Is Building These Apps

Many companies are now racing to build these powerful AI tools. Each company has its own version or plan:

Google recently launched “AI Mode,” which adds AI chat features to its regular search engine. Instead of just giving links, Google now gives direct answers and helpful suggestions.

OpenAI (the creator of ChatGPT) is working on turning ChatGPT into a personal assistant that can remember past conversations, do web searches, and even book appointments for you.

Microsoft is putting AI into tools like Word, Excel, and Teams. They call it “Copilot,” and it helps people write emails, summarize documents, or organize meetings.

Apple is believed to be working on adding more AI to Siri, making it smarter and more useful across all Apple devices.

Amazon is improving Alexa to become more human-like and better at understanding complex questions or commands.

Meta (Facebook) is creating AI avatars that can help users in social media, virtual reality, and more.

All of these companies have the same goal: to become your go-to assistant — the first thing you open when you wake up and the last thing you use before going to bed.

Why Are These Companies Doing This?

There are three main reasons why Big Tech wants to win the AI race:

1. Business Control

If one company controls your AI assistant, it controls the way you interact with the digital world. That means more money from ads, services, and sales. For example, if your AI assistant always suggests Amazon products, you’ll probably buy from Amazon.

2. Data Collection

These everything apps need to learn from your behavior. The more you use them, the more they know about your life, your choices, your likes and dislikes. This data helps them become better, but it also helps the companies target you with products and ads.

3. Staying Ahead

Big Tech doesn’t want to fall behind. If one company builds a perfect everything app and others don’t, people might stop using the slower or older tools. That’s why companies are rushing to release their own version of AI assistants.

What Can These AI Assistants Do?

These new AI apps are designed to do many complex tasks, such as:

Write emails or reports

Translate languages

Answer questions using the latest web data

Book hotels, restaurants, or flights

Chat like a human

Help with school or work

Offer fashion or health advice

Recommend movies or songs

Plan events or budgets

Manage your calendar and reminders

Some AI assistants even talk using voices that sound human, and they can remember what you told them last week or last month.

The Power of Personalization

One of the strongest features of these AI apps is personalization. That means they learn from you and adapt to your needs.

For example:

If you are a college student, the AI might help you study and take notes.

If you’re a parent, it might help organize your family schedule or buy groceries.

If you’re a small business owner, it might help with accounting, emails, or customer support.

The AI becomes your personal helper, like a digital assistant who knows your life inside out.

The Risks and Concerns

Even though everything apps sound amazing, they also come with big challenges and risks.

1. Privacy Issues

These AI assistants need to collect a lot of personal data to work well. That means your search history, emails, voice recordings, and even your location may be shared with tech companies. People worry that this could lead to spying or data misuse.

2. Mistakes and Errors

AI isn’t perfect. Sometimes it gives wrong answers or makes things up. If you trust it too much, it might give you bad advice — like wrong medical tips or incorrect news.

3. Control and Monopoly

If one or two companies own the most powerful AI assistants, they could control much of the internet. That could reduce competition and make it harder for smaller companies to grow.

4. Addiction and Over-reliance

If people use AI for everything, they might stop thinking for themselves. There’s a risk that we could become too dependent on machines, and forget how to do simple tasks.

5. Job Impact

As AI assistants become smarter, some human jobs might disappear — especially in areas like customer service, writing, or tech support.

What Happens Next?

We are still at the beginning of this AI revolution. Big Tech companies are working fast, and every few months, we see new tools and updates.

Soon, your AI assistant may be built directly into your phone, car, or even smart glasses. It might talk to you in your own voice, schedule your life, and help you with every task — big or small.

But with great power comes great responsibility. These tools will only be useful and safe if we build them with care. Companies, governments, and users need to work together to make sure that AI helps people and doesn’t harm them.

Final Thoughts

The race to create the ultimate AI assistant — the everything app — is changing the tech world forever. Big Tech companies want to be the leader in this new space because it will decide who controls the future of digital life.

These AI assistants promise to make life easier and more efficient. But at the same time, they raise big questions about privacy, fairness, and the role of technology in our lives.

As users, we need to stay informed, be careful with our data, and always remember that technology is here to assist us, not control us.

Thursday, 29 May 2025

Top 10 largest artificial intelligence companies in the world

Top 10 largest artificial intelligence companies in the world

In recent years, artificial intelligence has gained the interest of several companies and startups. Discover the list of the largest organizations in the world specializing in AI.

Among other technologies, artificial intelligence has become an almost indispensable element in our daily lives. From home to our workplace or schools, it is used in various ways to make certain tasks easier for us. Gartner estimates that the global AI software market is expected to reach a value of $62.5 billion by the end of 2024. Large organizations have understood this and are investing in research and development around this technology.

Here is a list of the largest artificial intelligence companies in the world.



Top 10 Artificial Intelligence Companies

Amazon Web Service

Amazon isn't just an e-commerce giant. It's also a leader in AI, with products like Alexa, its intelligent personal assistant, and AWS (Amazon Web Services). The AWS portfolio includes more than 200 services for computing, database and infrastructure management, application development, and security. On its cloud platform, Amazon also provides tools for governance, big data management, and AI .

Users include government agencies, private and nonprofit organizations, and educational institutions. Amazon Web Services currently serves businesses and artificial intelligence software developers in nearly 190 countries. In 2021, AWS products and servers generated $62.2 billion in revenue .

Microsoft Azure

Microsoft Azure is one of the main competitors of AWS with a revenue of more than $60 million in 2021. The platform offers SaaS (Software as a Service), IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and serverless computing services .

In other words, Microsoft Azure provides tens of thousands of tools and services for developing and scaling new AI applications. This includes computing, data analysis, storage, and networking. The platform also allows existing programs to be run in the public cloud.

Azure services are designed for businesses across all industries that want to leverage artificial intelligence . Furthermore, the tools are compatible with various open source technologies.

IBM Cloud

IBM also has its cloud division, which provides more than 190 PaaS and IaaS services. The Infrastructure as a Service division allows users to access computing power, storage, and networking over the internet. The company offers both virtual and non-virtual servers.


IBM Cloud PaaS, on the other hand, supports the management, execution, and deployment of applications for the public cloud. In terms of artificial intelligence, the platform also supports IBM Watson services such as Watson Assistant, Watson Studio, Watson Language Translator, Watson Discovery, and more.

In addition to AI/ML, IBM's cloud services also include quantum computing , the Internet of Things (IoT), and blockchain. The platform provides tools for logging and monitoring. Finally, it offers multiple SQL and NoSQL databases and analytics tools such as Apache Spark, Apache Hadoop, and IBM Watson Machine Learning. 


Facebook AI Research (FAIR)

Facebook AI Research (FAIR) is the artificial intelligence research arm of Meta Platforms Inc., formerly known as Facebook. Launched in 2013, FAIR focuses on understanding and improving the capabilities of AI systems by exploring areas such as computer vision, natural language processing, and machine learning. FAIR's goal is to push the boundaries of AI to improve the user experience on Meta platforms, such as Facebook, Instagram, and WhatsApp.

FAIR has developed innovative technologies such as DeepText , a real-time text understanding engine, and Mask R-CNN, a framework for object detection and image segmentation. In addition, FAIR contributes to the scientific community by regularly publishing its research and collaborating with universities and research institutes around the world. These efforts not only improve Meta's products, but also advance the field of AI as a whole, making advanced technologies more accessible and beneficial for everyone.


Google Cloud

Part of Alphabet Inc., Google AI is at the forefront of AI research. Known for developing TensorFlow, the open-source platform that democratized machine learning by making it accessible to developers, Google continues to push the boundaries with projects like Google Brain and DeepMind.

In 2022, Google Cloud generated revenue of $26.3 billion, solidifying its position as a leader in the cloud computing market. Like any cloud platform, Google Cloud provides a comprehensive suite of tools and services for computing, storage, application development and integration, and networking. Google Cloud also supports big data , machine learning , and IoT.


Among the flagship products offered by Google Cloud are:

  • Compute Engine for Infrastructure as a Service (IaaS).
  • App Engine for Platform as a Service (PaaS).
  • Cloud Storage for storing large data.
  • Cloud Datastore for NoSQL databases.
  • Cloud SQL for MySQL and PostgreSQL.
  • Cloud Bigtable , Google's native database, optimized for applications requiring low latency and high throughput.

Additionally, Google Cloud offers advanced tools for container and cluster orchestration, including Google Kubernetes Engine (GKE) , which has become a standard in container management.


NVIDIA

While the top five AI companies are cloud platforms, NVIDIA ranks sixth. Founded in 1993, it manufactures graphics processing units (GPUs) that are currently used by the largest technology companies.

While NVIDIA products are a huge hit with gamers, they are also recognized by scientists and researchers. GPUs provide parallel processing capabilities that enable high-performance computing applications. Some of the world's most powerful supercomputers are powered by NVIDIA GPUs.

These processors also power autonomous driving systems developed by companies such as Toyota and Tesla. Additionally, NVIDIA collaborates with cloud service providers such as Baidu and Google Cloud to optimize the performance of their infrastructures.

In 2022, NVIDIA generated an impressive $26.91 billion in revenue , highlighting its continued growth and critical role in the development of artificial intelligence and advanced technologies. This growth reflects not only the importance of GPUs in gaming, but also their indispensable role in scientific research, self-driving cars, and cloud services.


Databricks

It is an American technology company founded by the creators of Apache Spark. It offers a unified data processing and artificial intelligence platform called Lakehouse . This combines the advantages of a data lake and a data warehouse.

This approach allows companies to centralize their data , simplify their architectures and develop machine learning and AI models more efficiently.

Databricks' strength lies in its ability to handle massive volumes of data. At the same time, it facilitates collaboration between data scientists, engineers, and analysts through an interactive notebook environment . Currently, the platform supports languages ​​like Python, SQL, Scala, and R. Additionally, it integrates with open source tools like MLflow, Delta Lake, and, of course, Apache Spark.

Databricks also stands out for its scalability, multi-cloud compatibility (AWS, Azure, Google Cloud), and advanced data governance features. Many large enterprises are now adopting it for predictive analytics, fraud detection, product recommendations, and much more.


In 2023, Databricks surpassed $1 billion in annual recurring revenue . This is a testament to its pivotal role in the AI ​​and Big Data ecosystem. We can therefore say that it is a key player for data-driven organizations.


Alibaba Cloud

We're back in the clouds. Alibaba Cloud, also known as Aliyun, is a division of Alibaba Group, one of the world's largest technology companies. Founded in 2009, Alibaba Cloud has quickly evolved to become a leader in cloud computing and artificial intelligence (AI). In 2022, the company generated annual revenue of $11.76 billion , solidifying its leading position in the global market.

Alibaba Cloud is a leading player in the AI ​​and Big Data space. The company offers advanced artificial intelligence services that help businesses transform their data into actionable insights. Key services include:

  • Machine Learning Platform for AI (PAI) : A platform that facilitates the creation, deployment and management of machine learning models.
  • DataWorks : A big data workflow management tool that allows businesses to plan, develop, and manage their data projects.
  • Image Search : An image recognition service that allows users to search for products by simply uploading a photo.

OpenAI


OpenAI is an artificial intelligence research organization founded in 2015 by Elon Musk, Sam Altman, Greg Brockman, Ilya Sutskever, John Schulman, and Wojciech Zaremba. Created with the mission of promoting and developing AI that benefits humanity , OpenAI is distinguished by its ethical and transparent approach. The organization's goal is to ensure that advances in AI benefit everyone and are not dominated by a few powerful entities.


OpenAI is particularly known for its advances in natural language processing, notably with the development of GPT (Generative Pre-trained Transformer) models. The GPT-3 model, for example, demonstrated exceptional capabilities in text generation, translation, and question answering, which revolutionized the field of conversational AI.

In addition to its technical contributions, OpenAI actively engages in publishing research and collaborating with other institutions to ensure an open and collaborative approach to AI. The organization also develops practical tools for developers and businesses , enabling easy integration of AI into various commercial and industrial applications. With a strong focus on safety and ethics, OpenAI strives to guide AI development in a responsible and equitable manner.


Automation Anywhere

Automation Anywhere, as its name suggests, provides automation solutions. It offers a cloud-based platform that enables the creation of RPA (robotic process automation) software using artificial intelligence. This includes both front-office and back-office automation. Automation Anywhere provides an intuitive, no-code user interface and offers several products that help businesses maximize their ROI.

The company also offers a digital assistant called AARI that allows employees to easily access RPA from different platforms, applications, or devices. For example, with the mobile app, users can control robots anytime, anywhere.


Artificial Intelligence Companies: The Other Leaders of the Future

Defined.ai

Defined.ai, formerly Defined Crowd, is a provider of artificial intelligence data, tools, and models for large, small, and medium-sized businesses. The company also offers professionals assistance in developing and deploying machine learning projects.

Anduril

The technology company Anduril was founded by the founder of Oculus. It specializes in creating security products and solutions using AI technologies and sensor fusion. Its clients include the US military and customs service, border patrol, and the British Royal Marines.

Rev.com

Rev.com combines artificial intelligence and human assistance to transcribe videos and podcasts. Its technology is especially popular with freelancers working from home.

Socure

Security is a major concern for businesses and artificial intelligence researchers. To combat fraud, New York-based Socure provides digital ID solutions. Last month, it won the Best Identity Verification Solution category at the FinTech Breakthrough Awards.

Pymetrics

Pymetrics is a dedicated recruitment and matching solution powered by artificial intelligence. Simply put, the company develops an assessment test. Based on this, AI creates a profile of an ideal candidate, promoting diversity, efficiency, and sustainable business results.

Emerging startups : a new era revolutionizing AI

Two startups in particular, Deepseek and LightOn, embody a new generation of innovative companies in the field of artificial intelligence. Each in their own way, they are pushing technological boundaries to shape the future of information processing .

Deepseek

Deepseek is an emerging startup specializing in generative artificial intelligence and natural language processing (NLP). It stands out for its advanced approach to creating models capable of competing with solutions from industry giants. Through its work on language model optimization and accessibility , Deepseek aims to democratize AI for various uses, particularly in business and research.

LightOn

For its part, LightOn takes a unique approach by combining artificial intelligence and optics . By developing revolutionary photonic-AI processors, this French company is positioning itself as a key player in the acceleration of massive computing . Its solutions enable ultra-fast data processing while reducing energy consumption. This makes it possible to meet the challenges of modern AI.

Together, Deepseek and LightOn exemplify the dynamism and innovation driving the AI ​​industry. Their technological advancements could fundamentally transform the way we harness and develop artificial intelligence.

FAQs about Artificial Intelligence (AI) companies

What is an artificial intelligence company?

This is a company that develops AI-based technologies . Examples include machine learning, natural language processing, and computer vision. These companies create innovative solutions for various sectors such as healthcare, finance, manufacturing, and entertainment.

What are the areas of application of AI in business?

AI is used in many sectors:

  • Health : Assisted diagnosis, medical image analysis, drug discovery.
  • Finance : Fraud detection, automated trading, risk management.
  • E-commerce & Marketing : Personalized recommendations, chatbots, customer behavior analysis.
  • Industry : Predictive maintenance, robotics, process automation.
  • Human Resources : Recruitment, CV analysis, performance management.

How do AI companies make money?

AI companies generate revenue by selling software as a service (SaaS) , licensing their models, or consulting services. They may also integrate AI into existing products such as search engines and voice assistants. Some companies also monetize their APIs by offering paid access to their artificial intelligence models.

What are the challenges these companies face?

Artificial intelligence companies face many challenges. First and foremost, there are ethics and regulations . Data protection, algorithmic bias, and the impact on employment are essential considerations in their operations. In addition, infrastructure costs remain high.

Furthermore, the industry is evolving rapidly. This means that competition is intense . This fierce competition is closely linked to the constant innovation in which AI evolves. Finally, it's worth noting that some AI technologies raise concerns about their use and reliability . Therefore, companies that create these AI-based tools still have a long way to go to achieve public acceptance .

How can a company integrate AI into its processes?

The adoption of AI in business is a gradual process . It begins with identifying repetitive tasks that can be automated. Then, AI uses off-the-shelf solutions, including chatbots and predictive analytics tools. Furthermore, adopting AI in business involves working closely with specialized companies to develop tailor-made solutions.

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