🤖 OpenAI’s GPT-5.6 Sol Beats Claude Mythos

OpenAI’s GPT-5.6 Sol edges out Claude Mythos 5 in agent coding with 88.8% vs. 88% on Terminal-Bench 2.1. The Sol Ultra variant scores 91.9%.

Sol matches Anthropic’s model in cybersecurity using three times fewer tokens. The US government restricts its release, which OpenAI opposes.

OpenAI plans wider API and Cerebras access in July. Officials previously blocked Anthropic’s Fable 5, showing ongoing regulatory hurdles.

@datasciencepulse 〰️

🤖 Claude controls robot dog 20 times faster

Anthropic tested Claude on a four-legged robot with tasks that human teams completed less than a year ago. Claude connected to the robot’s camera and sensors, wrote control code, and set up object detection in under 10 minutes.

Claude] was 37 times faster than humans without AI and nearly 19 times faster than humans with AI. It wrote ten times less code than the previous human+Claude team, with most working on the first try.

@datasciencepulse 〰️

🇪🇺 Europe wants Anthropic on its own turf

Europe is starting to treat frontier AI like critical infrastructure.

According to Reuters, Austria is urging the EU to convince Anthropic to establish part of its business inside Europe, with EU laws, customers, capital, and infrastructure to reduce the bloc’s dependence on US-controlled AI.

The problem? Moving servers to Europe doesn’t move control.

Anthropic is still an American company, and its ownership, model governance, key employees, and training infrastructure remain subject to US export controls. That means Washington could still restrict access to its most advanced models for foreign users.

Austria’s argument isn’t that this is easy, it’s that Europe shouldn’t rely entirely on AI systems that could become unavailable because of a US political decision.

Source.

@dztasciencepulse 〰️

🇺🇸 U.S. data center spending now surpasses most infrastructure projects

U.S. spending on data center construction has reached $50 BILLION, now exceeding the COMBINED spending on airports, ports, and mass transit, per Bloomberg.

The AI infrastructure boom continues to accelerate, with US data center construction spending up 357% since 2022 and now accounting for 2.3% of all U.S. construction spending.

@datasciencepulse 〰️

💸Oracle just crossed a major milestone in the AI era.

For the first time, an S&P 500 company has explicitly linked mass layoffs to AI in an SEC filing.

Oracle cut 21,000 jobs, about 13% of its workforce and took a $1.8 billion restructuring charge, saying AI adoption is driving the changes.

The productivity gains are staggering. Internal pilots reportedly shrank teams of 47 database administrators to just 3 senior architects supported by AI. The system catches 94% of issues before they become problems, while engineering tasks that once took 6 weeks now take just 6 hours.

But this isn’t simply about cutting costs.

Oracle is redirecting those savings into a $50 billion AI infrastructure expansion for fiscal 2026, pouring money into data centers, GPUs, and cloud capacity.

@datasciencepulse 〰️

🤖Grok 4.5 has been developed using xAI’s new V9 foundation model, which contains 1.5 trillion parameters and incorporates data from Cursor. This makes it roughly three times larger than its predecessor, the v8-small model, which had 0.5 trillion parameters.

The V9 foundation model is described as a strong, reliable system comparable to Opus, rather than bringing a sudden leap in performance.

Notably, the pace of advancements at SpaceXAI has accelerated, following a shift in focus by several leading engineers from Starlink and Starship projects to artificial intelligence development.

The previous v8 model, used for Grok 4.3, was completed in December with several significant limitations. Grok 4.5 is expected to represent a substantial improvement in capability.

@datasciencepulse 〰️

🔍 Gemini now searches and buys apps in Play Store

Google integrated Play Store into Gemini, letting users find apps by simply telling the AI what they need. For example, saying "map for travel abroad" prompts Gemini to locate and open the app page directly.

Gemini also enables buying Play gift cards and in-game items right in chat. This feature is limited to personal Google accounts, users 18+, and is rolling out gradually on Android.

@datasciencepulse 〰️

💧 A fact-check regarding artificial intelligence’s water consumption, with focus on the impact of data centers, has emerged.

Available data suggests that large AI models and the facilities housing them require notable amounts of water, particularly for cooling equipment during intensive computations. This operational need has led to increased scrutiny of the technology sector’s environmental footprint.

Sources underline that water usage figures can vary depending on the location, the type of cooling technology used, and the demand placed on data centers. Reliable quantification is challenging, as not all companies disclose detailed consumption data. Nonetheless, the topic continues to attract attention as AI development accelerates.

@datasciencepulse 〰️

🧠 Meta unveils Brain2Qwerty v2: AI can turn brain signals into text, no brain implant required

Imagine typing… without actually typing.

Meta has demonstrated Brain2Qwerty v2, an AI system that converts brain activity into text using a non-invasive magnetoencephalography (MEG) helmet instead of a surgically implanted brain chip.

Here’s how it works:

🪖 The user wears an MEG helmet that measures the tiny magnetic signals produced by the brain.
🧠 As the person thinks about typing, the AI filters through the noisy brain activity.
⌨️ The model reconstructs the intended keystrokes and generates coherent sentences.

The technology is still confined to research labs because MEG scanners are large, expensive, and require highly controlled environments. It’s nowhere near replacing a laptop or smartphone keyboard yet.

Still, it’s a major step for non-invasive brain-computer interfaces. While companies like Neuralink rely on implanted electrodes, Meta is exploring whether AI can decode thoughts without surgery.

@datasciencepulse 〰️

🇰🇷 Korea is quietly becoming the world’s humanoid robot factory.

Goldman Sachs Research estimates Korean companies could produce 30% of all humanoid robots by 2035, jumping from virtually zero today to more than 412,000 robots a year. The reason? Decades of automotive manufacturing have given Korea the motors, actuators, supply chains, and factories needed to scale humanoids.

The government is fueling the push with ₩700 billion ($500M) for robotics in 2026, aiming to produce 1,000 domestically built humanoids annually by 2029.

Investors have already noticed. LG Electronics is leveraging its massive motor business to supply humanoid robots, Hyundai Motor is combining its manufacturing muscle with Boston Dynamics, while Hyundai Mobis, Rainbow Robotics, Robotis, and Doosan Robotics are all positioning themselves across the humanoid supply chain.

For broader exposure, Korea’s new humanoid robot ETFs have surged in popularity, with pension funds pouring billions into the sector.

@datasciencepulse 〰️

🧿 We can all relate.

@datasciencepulse 〰️

🇨🇳 Ex Meta PM and AI founder Xiaoyin Qu says “American and European enterprises will ditch OpenAI and anthropic and adopt Chinese models.”

@datasciencepulse 〰️

🔥The race to dominate enterprise AI 

Anthropic's recent surge has propelled it past OpenAI to become the leading paid AI provider for U.S. businesses, marking a shift in the AI race from model superiority to workflow dominance.

@datasciencepulse 〰️