Asian governments react to Nvidia CEO Jensen Huang’s exit
Some governments moved to confirm chip supply commitments, while others are monitoring the impact on local projects or addressing ongoing investigations.
#Data and training
#Data and training
0 todayNov 15
Nov 14
Amazon has a plan to index the world’s online shopping data
Amazon has plans to build a vault of data on every product sold anywhere on the internet, even products Amazon doesn't sell, and make the information available through its own site, according to Reuters.
Production MLOps at GS Caltex with Amazon SageMaker Canvas, part 1
GS Caltex connects Amazon SageMaker Canvas to Amazon SageMaker Pipelines so process engineers' no-code models run in production. This post shows how ML engineers reuse validated preprocessing flows and models, cutting deployment from about a week to a few hours and running batch inference every 30 minutes.
OpenFold3 on Amazon SageMaker JumpStart: Predict biomolecular structures
Deploy OpenFold3-preview from Amazon SageMaker JumpStart to predict 3D structures of proteins, DNA, RNA, and ligand complexes in your own AWS account. The post covers asynchronous inference, multi-GPU parallelism, bringing your own MSAs for accuracy and privacy, and scaling to zero to reduce cost.
Build a model improvement flywheel with Amazon SageMaker HyperPod Data Capture
Amazon SageMaker HyperPod Data Capture records live inference inputs and outputs to Amazon S3. This post walks through one end-to-end example: capturing a support router's production traffic, surfacing a new-product blind spot with Amazon Athena, fine-tuning on the captured data with the HyperPod training operator, and measuring the before-and-after lift.
Cost attribution and controls for AI developer and productivity tools on Amazon Bedrock
Amazon Bedrock provides built-in, zero-instrumentation cost attribution that traces every inference call back to the IAM principal that made it. This post shows how to attribute per-user Bedrock costs for AI developer and productivity tools using IAM Identity Center, session tags, and CUR 2.0, and how to enforce per-user usage limits.
Export-banned Nvidia chips are behind China’s most powerful AI models — uh-oh, Jensen!
New research shows the most advanced AI models from China were trained on banned Nvidia chips.
Former OpenAI researcher says he found Nvidia Blackwell fingerprints hidden inside six Chinese AI models
Former OpenAI researcher Will DePue says he has produced the first technical evidence that DeepSeek, Moonshot AI, MiniMax, and Ant Group are using Nvidia's latest Blackwell GPUs despite US export controls. His forensic method reads characteristic chip signatures directly from published model weights. He estimates the hardware behind the five training runs cost more than half a billion dollars.
Nov 13
How AI Is Helping Care Teams Get Patients the Right Care, Sooner
From pediatric research to smart hospitals, AI is helping care teams spend less time on routine tasks and more time with patients. Health systems and startups are putting it to work across healthcare, from matching patients to clinical trials to supporting radiologists, hospital teams and patients at home.
How Natera designed an agentic AI system for lab ops with Amazon Bedrock AgentCore
Natera built SWARM, an agentic AI system on Amazon Bedrock AgentCore that captures institutional lab-operations knowledge and deploys it at scale. This post walks through the full architecture, from knowledge base construction to deployment and evaluation, delivering about 130x faster first response and 96.2% automated coverage across support tickets.
Nebius tests the neocloud playbook with $40 billion in planned spending
Nebius plans to fund its $40 billion AI infrastructure expansion through customer prepayments and loans, even as delays at a Microsoft data center raise questions about its financing model.
LLMON: An LLM-Native Markup Language, now in Granite 4.1 3B and 8B
LLMs rely on their context to generate the next set of tokens. To address this, we developed LLMON (LLM Object Notation, pronounced “lemon”), an LLM-native markup language for explicitly communicating structure and semantics to the models.
Tokenomics at scale: Track and cap Amazon Bedrock spend per IAM principal with CUR 2.0 and AWS Budgets
Get per-identity Amazon Bedrock cost visibility and enforceable spend limits using only AWS-native features, with no application code for the common case. Attribute spend with IAM principal tags, report with CUR 2.0 or Cost Explorer, and enforce with AWS Budgets actions that apply a Deny policy when a threshold is crossed.
Jensen Huang is out. What did China want from him?
Today, we’re talking about the Jensen Huang scandal at Nvidia, which is developing so quickly that we had to do an emergency update of this intro minutes before publishing this episode.
Cyberattack on Fireworks AI allowed hackers to access Notion customers’ chat transcripts
This is Fireworks' second data breach in as many months.
Nov 12
Google Deepmind shifts genomics AI from bulk tissue predictions to single cell type resolution with AlphaGenome 2
Google Deepmind has unveiled AlphaGenome 2, an AI model that analyzes genetic variants for individual cell types rather than across bulk tissue. Trained on more than 107 million cell profiles, it identifies nearly twice as many disease-relevant gene changes as its predecessor.
Detecting and recovering from silent data corruption on Amazon SageMaker HyperPod
Silent data corruption is a GPU fault that returns wrong but plausible numbers with no error, quietly poisoning distributed training. This post adds three checks to a PyTorch DDP loop to detect it, localize the faulty node on Amazon SageMaker HyperPod, and hand the node to automatic recovery for replacement.
Using wearables to enable cardiovascular-kidney-metabolic (CKM) risk profiling for personalized coaching
Heart disease, kidney conditions, and metabolic disorders like type 2 diabetes aren't isolated, they form an interconnected web known as cardiovascular-kidney-metabolic (CKM) syndrome . CKM progression often begins silently years before symptoms appear, shaped by everyday habits like movement, sleep, and cardiovascular activity.
The attendee’s guide to the AWS re:Invent 2026 AI/ML track
AWS re:Invent 2026 includes more than 140 AI/ML track sessions. This attendee's guide helps you find the breakouts, chalk talks, workshops, and builders' sessions that fit your role and goals, spanning AI chips, models and inference, agents, agent trust, and sustainability, so you can build a smarter re:Invent schedule.
With $720M round, Britain’s Fractile gets a leg up in the race for AI chips
Fractile has now become one of the top-funded players in the race for purpose-built AI chips.
Meta is losing its longtime head of infrastructure
Santosh Janardhan, who originally joined the company in 2009, will be stepping down from his role.
Anthropic's IPO roadshow video
Anthropic's IPO roadshow video Anthropic kicked off their IPO roadshow yesterday, and their roadshow video has some previously unreleased information about how their business works. The section on "Approach to compute" with co-founder Tom Brown is particularly interesting, describing how Anthropic train and serve Claude across AWS Trainium, Google TPUs, NVIDIA GPUs, and AMD GPUs.
Databricks’ new AI agent tells CEO Ali Ghodsi the unvarnished truth
With Databricks at 12,000 employees, AI Ghodsi is the first to admit that he can't know everyone and that they are unlikely to confess the things that go wrong to him. But he doesn't need them to. He uses Databricks' newly revised Genie agent for that.
Nov 11
US data brokers are selling half a billion dollars in RL training environments to Chinese AI labs
US data brokers like Mercor, Surge AI, and AfterQuery are selling roughly half a billion dollars' worth of AI training data to Chinese labs, according to a ChinaTalk investigation. That includes the same RL environments previously built for OpenAI or Anthropic. At least nine firms are involved, and export controls barely apply.
Token Pooling-Aware Training for Multi-Vector Embedding Models
Multi-vector embedding models give each query token its own opportunity to find a match in a document. With pool_factor=4 , my normally trained model retains 94.6% of its unpooled NanoBEIR nDCG@10, with a 4x reduction in document vectors. Token pooling-aware training raises that retention to 97.8% at the same storage budget!
AlphaGenome 2: Deciphering how cells read DNA to better understand disease
Predicting how DNA sequences and their variations impact specific human cell types and disease.
Plurai wants to help AI agents work better using the same approach that helped get self-driving cars to roads
Like the end-to-end models trained to drive cars, AI agents are probabilistic systems operating in unpredictable environments.
Google’s AlphaGenome 2 zooms in on the cellular roots of disease
Researchers at Google DeepMind have unveiled a new AI model designed to unravel how changes in our DNA affect different cells, giving scientists a more detailed view of a notoriously difficult problem that could hold important clues to the causes of disease - and point the way to new treatments.
[AINews] Mercor $750m Series D at $20B valuation, $3B run rate
We missed Mercor’s $10B Series C last year when it had less than $500m in revenue, but knew we wouldn’t have to wait too long til the next round, since it crossed $1B in Feb and $2B in June , it has now hit $3B annualized, surviving hacks : View post on X ↗ The company reports 5 million experts, and their TAM: “In the United States alone, there are more than 800 distinct occupations, each containing workflows that models have yet to be evaluated against.”
Nvidia's model GR00T 2 watches humans on video, then imagines itself as the robot
Nvidia's new AI model GR00T 2 is designed to teach robots new tasks without laborious teleoperation. Instead, the system transfers human hand movements from videos to robotic arms, trained on about 400,000 hours of video footage. Success rates still vary widely, though, ranging from 10 to 80 percent depending on the task.
Amazon Bedrock tokenomics data lake
Running Amazon Bedrock across many accounts shows you the bill but not what happened inside each call. This post builds a centralized observability data lake that aggregates Bedrock invocation logs from every linked account into one queryable table, so you can see prompts, token counts, model choice, and per-invocation cost across your organization.
Nov 10
Ukraine’s fiber-optic drones get squeezed by AI data center demand
Ukraine competes with Russia and data centers for China’s optical fiber supply.
The global pledge to use AI for climate good is a cruel joke
At this point, reading through the latest splashy pledge to use AI for the good of the environment feels like downing a nonalcoholic beer. Admittedly, I'm suspicious from the onset. How can this be good?
Opening the datasets behind our AI weather models
Foundational precipitation and geostationary satellite datasets to observe the planet clearly.
What could China get from Jensen Huang?
It's difficult to overstate Nvidia's power in today's AI landscape. The company's chips are the bedrock upon which advanced AI technology in the US is being built, and demand has consistently outpaced supply for years.
What Frontier Labs Buy: A Data Deep Dive with Handshake AI — Garrett Lord & Team
Handshake went from launch to $1B in one year pushing the envelope of specialized data for frontier labs. Our first deep dive into a data lab with specific examples across Finance, Bio, and Alignment
Nemotron-Personas-Finance-Japan: A Synthetic Dataset Capturing Japan's Demographics and Financial Context
To address these challenges, Elith and NVIDIA have released Nemotron-Personas-Finance-Japan , a financial domain extension of the open-source persona dataset " Nemotron-Personas-Japan ." To our knowledge, it is the first open persona dataset at million-record scale that pairs Japan’s official statistics with household finance and financial literacy data.
Nov 9
Innovating with AI in the special chemicals industry
As companies look to accelerate innovation with artificial intelligence, cloud computing, and advanced modeling, the primary challenge is connecting new technologies to reliable data, scientific expertise, and the practical realities of bringing products to market.
Nov 8
The inventor of the bitter lesson has a bitter lesson for LLM scaling enthusiasts
Turing Award winner Richard Sutton reaffirms that raw compute alone isn't enough for intelligence and that fundamentally new learning methods are needed. Ex-OpenAI researcher Tworek agrees, saying blind transformer scaling "has reward hacked brains of a whole generation of scientists." A growing wave of startups is already betting on exactly this gap.
Nov 7
State propaganda in some Chinese AI models is only "a thin layer" that fine-tuning can strip away
Nous Research retrained Alibaba's Qwen3.8-27B to produce Arete-27B, largely stripping out its pro-Chinese bias. The propaganda rate dropped from 22 percent to less than one percent, while general capabilities remained intact in tests. The method relied on 53 million tokens of supervised fine-tuning. The political bias is "applied late, it is applied thin," the team writes.