🧠 Elon Musk says every genius in history had one thing in common: they all ran on the same brain.

For roughly 50,000 years, human intelligence barely changed. The same biological hardware powered everyone from prehistoric hunters to Einstein.

Then AI arrived.

Musk recalled how experts once believed beating the world’s best Go players was decades away. Instead, AlphaGo went from defeating one champion to reaching a level where it could take on dozens of elite players at once without breaking a sweat.

The point isn’t Go. It’s the pace.

AI doesn’t get tired. It doesn’t forget. It improves at a speed biology can’t match.

For thousands of years, every breakthrough depended on the limits of the human mind. Today, those limits matter less than ever because intelligence is becoming something we can build, scale, and improve.

@datasciencepulse 〰️

Ⓜ️ Meta’s upcoming AI model, internally codenamed Watermelon, has reportedly caught up with OpenAI’s GPT-5.5 on closely watched benchmarks.

Meta AI chief Alexandr Wang told employees that Watermelon is still training and uses roughly 10 times more compute than Muse Spark, the company’s current model family.

The exact benchmarks were not disclosed, so the claim cannot yet be independently verified.

Meta is also preparing an update to Muse Spark with stronger coding and agent abilities, while Wang says a model competitive with Claude Opus could arrive “pretty soon.”

@datasciencepulse 〰️

📃 Vibe-coders work on a $1 billion AI startup at 2 AM.

@datasciencepulse 〰️

🧑‍💻 GitHub Sells Repos on CD-ROM

GitHub now offers copies of repositories on CD-ROM.

Users can order physical copies to preserve code offline or for future use.

@datasciencepulse 〰️

📕 AI Godfather Geoffrey Hinton on why AI already outlearns the human brain despite us having 100x more neural connections.

@datasciencepulse 〰️

🚗Your car’s engine might soon tell you what’s wrong, just by listening.

A new open-source AI called CarDiag can detect potential car problems from the sound of your engine. Simply record your engine with your phone, upload the audio, and the model analyzes the recording to identify which vehicle system is most likely causing the issue.

It’s still early days. Right now, the AI correctly distinguishes between healthy and faulty engines about 79% of the time. But here’s the impressive part: the entire trained model is only around 100 KB, making it incredibly lightweight and easy to run.

Because the project is fully open source, the creator hopes developers and car enthusiasts will help train it into a much more accurate mechanic that fits in your pocket.

Source.

@datasciencepulse 〰️

📊 By 2027, just 5 companies, Alphabet, Amazon, Meta, Microsoft, and Oracle, are expected to spend around 3.2% of US GDP on AI capital expenditure.

That would put private AI infrastructure spending above US national defense spending, which is expected to be around 2.7% of GDP.

The AI race is now being funded at a scale normally associated with governments, wars, energy systems, railroads, highways, and telecom buildouts. The striking part is the speed. AI capex is expected to jump from about 1.5% of GDP in 2025 to about 2.5% in 2026, then to 3.2% in 2027.

AI boom is now large enough to influence the broader US economy significantly, it can move GDP growth, electricity demand, chip supply, construction activity, corporate debt markets, and ofcourse the labor market.

@datasciencepulse 〰️

🔥Hyundai Motor showcases its Atlas humanoid robot at the 2026 World Cup, with plans to manufacture 30,000 units annually in the US starting 2028.

@datascincepulse 〰️

🤖 Anthropic plans its own AI chip

Anthropic is in early talks with Samsung to develop a custom AI chip. The startup already uses AWS Trainium, Google TPU, and Nvidia GPU hardware but faces scaling challenges.

Anthropic builds AI models and needs more control over its infrastructure. Following OpenAI's lead, it aims to boost performance by designing dedicated silicon.

@datasciencepulse 〰️

🤖 Hackers Exploit LLM Hallucinations for Phishing

Unit 42 uncovered over 13,000 malicious URLs created by registering fake domains that large language models often hallucinate. These domains mimic real ones with patterns like name_download.com instead of.

This tactic, called Phantom Squatting, works like typosquatting but uses AI-generated fake URLs. The LLMs themselves suggest these phishing sites to users, removing the need for hackers to lure victims directly.

@datasciencepulse 〰️

📈 AI isn’t replacing creativity, it’s flooding the world with it.

A new analysis from The Economist reveals that since ChatGPT launched, generative AI has dramatically increased the amount of content being created across almost every major creative industry.

Books, music, software, scientific papers, and even legal documents are now being produced at a pace that would have been difficult to imagine just a few years ago. Amazon has seen a surge in AI-written e-books, music platforms are receiving tens of thousands of AI-generated songs every day, developers are shipping code faster with AI copilots, researchers are publishing more papers, and lawyers are using AI to draft documents in minutes instead of hours.

The result is a world where producing content is becoming incredibly cheap and incredibly fast.

But there’s a catch.

As AI removes the cost of creation, it also creates an overwhelming flood of information. Every day, the internet fills with more articles, videos, songs, apps, and documents than any person could ever consume. The challenge is no longer making content, it’s deciding what’s worth paying attention to.

Ironically, AI may not create a shortage of creativity. It may create a shortage of attention.

Source.

@datasciencepulse 〰️

🤖Looks like robots won’t be replacing soccer players any time soon…

@datasciencepulse 〰️

🖥 Microsoft is laying off another 4,800 employees as its massive AI ambitions reshape the company.

The cuts affect about 2.1% of Microsoft’s workforce, hitting commercial operations and the Xbox division. Microsoft says these jobs aren’t being replaced directly by AI but the company’s enormous AI spending is clearly driving the pressure.

Azure continues to grow rapidly, yet building the infrastructure to power AI is becoming incredibly expensive. Microsoft now expects to spend $190 billion in 2026, a figure that shocked analysts and highlights just how costly the AI race has become.

Xbox is feeling the squeeze too. Hardware costs have climbed, console demand has cooled, and even heavier investment in games hasn’t delivered the revenue boost Microsoft hoped for. Reports suggest Xbox operating margins are hovering around 3%.

Source.

@datasciencepulse 〰️

🤖 Anthropic reveals Claude’s silent thoughts

Researchers at Anthropic found Claude has internal areas linked to specific words that activate silently during processing. These spots hold words in mind without appearing in the output, emerging naturally during training.

For example, when asked about an animal spinning a web, the internal 'spider' area lit up even though the word wasn’t spoken. Changing this internal word to 'ant' changed Claude’s answer. The same spot swaps concepts like 'France' and 'China' to alter responses about capitals and currencies.

When prompted for blackmail, words like 'fake' and 'fictional' lit up inside Claude before it answered, showing awareness of a trap.

Anthropic says this is not consciousness but an emergent.

@datasciencepulse 〰️