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NYB.AI Launches Vecura 2.0, Bringing Agentic AI Workflows to Molecular Discovery, with NVIDIA
Life science research is entering an AI era, but most discovery teams still cannot use frontier models at scale. Advanced AI models, molecular simulation tools, scientific databases, inference optimization and GPU infrastructure remain fragmented across separate systems. For many pharmaceutical companies, ingredient innovators, biotech teams, and research groups, this makes AI adoption slow, costly, and technically demanding.
Why Broadcom (AVGO) Is Up 11.1% After New AI Data Center And Edge Network Platforms
TSLA Stock Weakens As Elon Musk’s Optimus Faces New Challengers
General AI
This News From Nvidia CEO Jensen Huang Could Shift the Stock Into Overdrive
Announcements from GTC Taipei confirm the company's continuing importance in the AI revolution.
Anthropic’s first-mover IPO edge set to widen lead over OpenAI
The first to tap the U.S. market's unparalleled depth and liquidity will likely gain an immediate advantage regarding chips, data centers and talent.
The ‘godfather of AI’ says we’re not just creating new beings — they’ll be much smarter than us, and soon
The race to make the smartest possible AI that can do the most things will "lead to things that aren't nice beings towards us," Geofrey Hinton said.
AI costs how much? GitHub Copilot users react to new usage-based pricing system
Some report burning through their whole monthly "AI credit" allotment in a single day.
Alphabet plans to raise $80B to pay for AI buildout
"The company is experiencing strong demand for its AI solutions and services from enterprises and consumers, at levels that are exceeding the company’s available supply," Alphabet said in its statement.
Anthropic confidentially files its S-1 first—but the IPO race with OpenAI is just beginning
As two AI giants hurtle towards IPOs, Anthropic is showing early momentum.
Transforming rare cancer research with Amazon Quick: Integrating biomedical databases for breakthrough discoveries
In this post, we walk through how to use Amazon Quick Research to integrate biomedical data sources for rare cancer research. The walkthrough uses pediatric sarcoma as the research domain and draws on publicly available datasets from PubMed and other open biomedical repositories. It covers the end-to-end workflow: defining a research objective, configuring data sources, reviewing the AI-generated research plan, running the investigation, and iterating on results using the revision and versioning system.
Amazon AI Blog
Microsoft to unveil new AI models and Windows improvements at Build
Microsoft is heading to San Francisco this week in a bid to win back developers at its Build conference. I've been attending Build since the days when Microsoft called it the Professional Developers Conference, and I can't remember a more pivotal moment. As Microsoft continues to reshuffle its entire business around AI, it's moving Build into a smaller, more intimate venue. Trust in Windows and GitHub is at an all-time low, and this is Microsoft's chance to reconnect with developers and outline the future. Sources tell me that we'll hear about new AI models in Windows, a new reasoning model from Microsoft AI, and a Copilot "super app." But … Read the full story at The Verge.
Anthropic files to go public
The company said Monday it has filed confidentially for an IPO.
Meta’s own AI was exploited to hijack Instagram accounts
Meta's AI support chatbot helped hackers hijack Instagram accounts, as reported earlier by 404 Media. In a video shared on Telegram, a hacker shows how they could take over an account by asking Meta's chatbot to switch the email associated with someone else's profile and then reset the password. The issue, which Meta says has since been patched, cropped up around the same time Barack Obama's White House account on Instagram was hacked. On Sunday, users noticed that the @obamawhitehouse account began posting images containing Iranian propaganda. Hackers appeared to have hijacked the Instagram accounts belonging to the US Space Force Chief Ma … Read the full story at The Verge.
Anthropic has officially filed to go public
After months of speculation about whether OpenAI or Anthropic would be first in their race to IPO, Anthropic on Monday reached a key milestone: filing to kick off the process with the U.S. Securities and Exchange Commission. The filing sets the stage for what's sure to be a massive IPO. As of its fundraise last week, Anthropic is being called the world's most valuable startup, with a post-money valuation of $965 billion. That tops the $852 billion post-money valuation of OpenAI, which is its biggest rival. Anthropic chose to submit its draft registration statement to the SEC confidentially, according to a blog post from the company, meani … Read the full story at The Verge.
Welcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
In an agent stack, where would you add heavy reasoning first: state corruption, tool-contract mismatch, or the last external action?
I keep thinking Ring-2.6-1T makes more sense as a containment layer than as a default model for every step. It is a trillion-parameter reasoning model for agent workflows with high and xhigh reasoning-effort modes. If I only added it to one failure-prone point first, I would choose state corruption, a tool-contract mismatch, or the final external action before the agent changes something outside the sandbox. Which failure point would you guard first? submitted by /u/Spirited_Friend_8428 [link] [comments]
New Fed study shows remote work, not AI, is driving higher unemployment in younger workers
The Federal Reserve Bank of New York found companies preferred to hire more experienced workers for jobs that can be done remotely as opposed to non-remote jobs.
Meet the people who actually want AI to replace humanity. (We need to create a new humanism before these “AI successionists” win!)
submitted by /u/vox [link] [comments]
AI news from 200+ sources
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Mediator finds Amazon caused first-contract impasse at YVR2, recommends binding path to agreement
An independent mediator has found that Amazon was responsible for the breakdown of first-contract bargaining at YVR2, its only unionized fulfillment centre in British Columbia. The mediator sided with the union and recommended the dispute be resolved through binding mediation-arbitration.
NVIDIA releases new and updated tools for physical AI developers
NVIDIA has released open-source physical AI agent skills and tools, as well as an Isaac GR00T humanoid reference robot. The post NVIDIA releases new and updated tools for physical AI developers appeared first on The Robot Report.
Gemini’s new AI agent is about as good as Google’s demo
Google's new "24/7" AI agent, Gemini Spark, can be shockingly good at doing things on your behalf. But I'm not sure it's worth the financial cost and potential privacy tradeoffs. The company gave me access to Spark last week. Google advertises Spark as an AI agent that can take on tasks and work on them in the background - even tasks that have multiple steps - allowing you to put your phone down or walk away from your computer. It also advertises at the very top of the Spark website that it's "always under your direction," that "you choose to turn it on," and that "it's designed to check with you before taking major actions." Given the moun … Read the full story at The Verge.
Nvidia chases $200B CPU market with AI agent PCs from Microsoft, Dell, and HP
If Nvidia has cracked a way to bring AI agents easily, safely and usefully to the masses, it could — and should — be big.
MiniMax-M3 debuts, eclipsing GPT-5.5 and Gemini 3.1 Pro on key benchmark performance for just 5-10% of the cost
Big news in enterprise AI broke over the weekend as Chinese AI startup MiniMax released its highly anticipated M3 large language model on Sunday evening Eastern time, pairing frontier-tier coding and agentic performance with a 1-million-token context window and native multimodality for a fraction of the cost of leading proprietary models, with pricing starting at just $20 per month under its new subscription token plans. The company's leadership also announced plans to deliver the model under an open source license including "open weights," allowing for full enterprise downloading and customizability free-of-charge, coming sometime in the next 10 days. For now, it is available via the MiniMax API at a special discounted price of $0.3 per 1 million input tokens and $1.20 per million output tokens (on fresh cache) for the next week — beating proprietary U.S. giants like Google, OpenAI and Anthropic handily on cost, while also eclipsing the performance of the latest models from the forme
Anthropic Confidentially Files for What Could Be the Largest IPO Ever
The AI giant behind Claude submitted paperwork on Monday that would take it public, just a couple of weeks after SpaceX’s splashy IPO announcement.
Nvidia unveils new ‘superchip’ for AI-driven home computing
The chips are designed to allow AI agents to become the primary way users interact with their computers, rather than a mouse and keyboard.
For AI agents, where should the heavier reasoning budget go first: before actions, after state changes, or before the final explanation?
One thing I find interesting about reasoning models is that the hard question is often budget placement, not headline capability. Ring-2.6-1T is a trillion-parameter reasoning model for agent workflows with high and xhigh reasoning-effort modes. If an AI agent only gets a heavier reasoning pass in one place, I would put it before it takes an external action, after it updates state, or before it gives the final explanation to a user. Where would you spend that budget first? submitted by /u/babyb01 [link] [comments]
For Ling-2.6-1T, what would make the size feel justified first: quality per token, local serving reality, or long context stability?
The first question I have about Ling-2.6-1T is not “is the model card impressive?” It is whether the boring trade-off makes sense. It is an open-sourced Ant/InclusionAI flagship with about 1T total params / 63B activated params, up to 1M native context, and 256K currently exposed through the official API. For a local-LLM crowd, I’d want one answer first: does the quality justify the active size, can the serving setup make sense, or does the long window stay stable enough deep into context? Which one would you need answered before caring about it? submitted by /u/Top_Training5738 [link] [comments]
Robotics
Mecka AI raises $60 million to train robots with human data sourced from body sensors and iPhones
The crypto VC Framework Ventures led two fundraises for the robotics startup, which projects $100 million in annual run rate.
Nvidia bets big on physical AI at GTC Taipei with a new world model, driving brain, and open humanoid robot
Nvidia used GTC Taipei to launch a series of models for robots, autonomous vehicles, and video systems. The centerpieces are the new world model Cosmos 3, a significantly scaled-up driving model called Alpamayo 2 Super, and an open reference platform for humanoid robots. The article Nvidia bets big on physical AI at GTC Taipei with a new world model, driving brain, and open humanoid robot appeared first on The Decoder.
Business & Industry
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