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If spending billions now leads to even bigger revenue later, plenty of capital wants that trade. "The economy hasn't seen something quite like this before". But model growth correlates directly with revenue growth
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It’s electronic skin,woven with dense fiber and textile sensors that can detect pressure, touch, deformation, and subtle contact changes in real time.
Now imagine humanoid robots covered in it,especially on dexterous hands. Humanoids could truly touch and understand the physical world and even humans.
~ Shanghai JQ INDUSTRIES
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Niantic says photos and scans collected through Pokémon Go and its AR apps have produced a massive dataset of more than 30 billion real-world images.
The company is now using that data to power visual navigation for delivery robots, letting them identify exact locations on city streets without relying on GPS.
Source: NewsForce
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The former OpenAI and Tesla AI leader just released an open-source project that scores how exposed every U.S. job is to AI automation.
Here’s how it works:
The dataset:
• Scraped 342 occupations from the U.S. Bureau of Labor Statistics
• Each job was evaluated using an LLM scoring rubric from 0–10
• Built an interactive treemap visualization
• Rectangle size = number of workers in that job
• Color = how vulnerable the role is to AI
The key rule behind the scoring
If the work product is digital and the job can be done entirely from a home office, the exposure score rises dramatically.
Some example scores:
• 0–1: Roofers, janitors
• 4–5: Nurses, retail workers, physicians
• 8–9: Software developers, paralegals, data analysts
• 10: Medical transcriptionists
Overall result: Average exposure across all occupations: 5.3 / 10
Fully open source, Karpathy also released the entire pipeline:
• BLS data scraping
• LLM scoring methodology
• The visualization system
Anyone can reproduce it or update the scores as AI improves.
https://github.com/karpathy/jobs
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"Either he believed it and was mistaken, or he was lying". It may push the team, but for engineers, hearing 'next year' again and again is demoralizing.
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They are training for their half-marathon! Over 20 teams joined the first trial run. The official race will be held on April 19.
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Researchers at Moonshot AI just proposed a new architecture tweak that could make large AI models more efficient and smarter about how they use information from earlier layers. Instead of the traditional residual connections used in deep networks, they introduce Attention Residuals, a system where each layer can selectively attend to representations from previous layers.
Here’s what’s new:
Attention over past layers:
• Traditional residuals simply add outputs from earlier layers in a fixed way.
• Attention Residuals let the model dynamically choose which earlier layers matter for a given input.
Solves depth dilution:
• In very deep models, useful information from earlier layers can get diluted.
• Attention-based retrieval allows the network to pull specific past representations when needed.
Block AttnRes for scale:
• Layers are grouped into compressed blocks so cross-layer attention remains computationally practical.
Efficient in practice:
• Reported 1.25× compute advantage
• <2% extra inference latency, meaning almost no slowdown.
Tested on the Kimi Linear model:
• Evaluated on 48B parameter architecture (3B activated parameters).
• Shows consistent downstream performance improvements.
Source.
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AI Post — Artificial Intelligence
Kimi just made AI notably cheaper to run. Open-sourced it. Put it out for free. Meanwhile OpenAI is asking people to pay $200 a month to use a model that already feels behind the curve.
Two Chinese labs. Both open source. Both doing more with less. Both giving away for free what American companies charge billions for.
The AI race isn't US vs China anymore... It's closed vs open. And closed is losing.
And the wildest part? Nobody in Silicon Valley will acknowledge this.. Because admitting a Chinese lab just moved the field forward for free destroys the entire "we need $10B to build AGI" fundraising pitch.
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Two Chinese labs. Both open source. Both doing more with less. Both giving away for free what American companies charge billions for.
The AI race isn't US vs China anymore... It's closed vs open. And closed is losing.
And the wildest part? Nobody in Silicon Valley will acknowledge this.. Because admitting a Chinese lab just moved the field forward for free destroys the entire "we need $10B to build AGI" fundraising pitch.
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80,000+ monthly listeners. Fans had it in their Spotify Wrapped top 5. Merch was selling. Then, community sleuths exposed it. Traced the creator's account to Europe. Spotted AI-generated hands in the music videos.
The creator's response? Recruit 7 real musicians from actual Tokyo bands to perform the AI-generated songs live. They've now played several live shows and have more on the books.
From an interview with the band's creator: "In an age where AI is taking everyone's jobs, this has actually created jobs. It's done the complete opposite."
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Aims to turn the chatbot into a serious tool for professional analysts. These experts will help Grok understand tricky concepts like leveraged loans and mortgage-backed securities and the specialized logic used by traders.
Source.
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Sam Altman just told a room of college sophomores that by the time they finish school, Artificial General Intelligence will be a reality.
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Elon just pledged to donate ALL his OpenAI lawsuit winnings to charity. He’s suing for $134 billion, that’s the entire value of OpenAI’s nonprofit… he wants it back..
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It’s electronic skin,woven with dense fiber and textile sensors that can detect pressure, touch, deformation, and subtle contact changes in real time.
Now imagine humanoid robots covered in it,especially on dexterous hands. Humanoids could truly touch and understand the physical world and even humans.
~ Shanghai JQ INDUSTRIES
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Futurist Ray Kurzweil predicts: by 2030, humans could be closer than ever to immortality, thanks to nanobots.
Ray’s been right about ~86% of his past predictions. This could be his boldest yet.
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Ray’s been right about ~86% of his past predictions. This could be his boldest yet.
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GPT-5.4 mini is available in ChatGPT, Codex, and the API.
Optimized for coding, computer use, multimodal understanding, and subagents. And it’s 2x faster than GPT-5 mini.
https://openai.com/index/introducing-gpt-5-4-mini-and-nano/
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Optimized for coding, computer use, multimodal understanding, and subagents. And it’s 2x faster than GPT-5 mini.
https://openai.com/index/introducing-gpt-5-4-mini-and-nano/
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Highlights:
Self-evolving - first model that helped build itself, running 100+ autonomous optimization loops during its own RL training (30% internal improvement).
Strong coder - 56.2% on SWE-Pro (near Opus 4.6), 55.6% on VIBE-Pro, production debugging down to under 3 minutes.
ML research agent - 66.6% medal rate on MLE Bench Lite, tying Gemini 3.1.
Office work - top open-source ELO on GDPval-AA (1495), 97% skill adherence, can do end-to-end analyst workflows (reports, models, PPTs).
Native multi-agent and a new open-source interactive character demo called OpenRoom.
https://www.minimax.io/news/minimax-m27-en
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A major AI power struggle is brewing between Microsoft, OpenAI, and Amazon over a massive cloud deal that could reshape the AI infrastructure stack.
What’s happening:
• Microsoft is considering suing over a $50B+ OpenAI–Amazon cloud partnership
• Dispute centers on whether Amazon Web Services can host OpenAI’s new product Frontier
• Microsoft claims this could violate its exclusive cloud agreement with OpenAI
The core conflict:
• Microsoft’s deal requires all OpenAI model access (APIs) to go through Microsoft Azure
• Amazon + OpenAI say they’ve built a workaround using a “stateful runtime” layer
• Microsoft argues: The workaround isn’t technically valid, even if it works, it breaks the spirit of the contract
What Frontier is:
• OpenAI’s new enterprise platform for autonomous AI agents
• Designed to: Remember context (stateful memory), operate across tools + company data, run complex workflows inside businesses
• It’s the centerpiece of the Amazon partnership
Behind the scenes:
• Weeks of legal clashes over definitions like:
• “Stateless” (raw model access)
• “Stateful” (apps with memory layered on top)
• Amazon is being extremely careful:
• Staff are banned from saying AWS gives access to OpenAI models directly
• Language like “powered by” is allowed but not “calls OpenAI”
A lawsuit could: Disrupt OpenAI’s planned IPO, add to existing legal pressure (including Elon Musk’s lawsuit against Sam Altman). OpenAI still needs massive capital to fund compute and AWS is a key partner
The real battle isn’t just AI models, it’s who owns the infrastructure layer they run on.
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