Introducing Images 2.6
Images 2.6 brings faster image generation, GIF creation, more precise editing, and new API controls across ChatGPT, Codex, and the API.
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[AINews] Anthropic ends Coding Interviews: "Hunger beats tenure"
Since coding is solved, why code for the job?
Using AI for Analog Design
The growing role of AI in analog and mixed-signal design, where complexity is rising, schedules are tightening, and the cost of mistakes is higher than ever. The post Using AI for Analog Design appeared first on Semiconductor Engineering.
VCs will make billions on Anthropic’s IPO, but Amazon is set to make much (much) more
Massive note conversions reveal the true extent of Amazon's ownership in Anthropic.
NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt
NVIDIA Nemotron 3.5 Transcribe and Granary v2: Intelligent Multilingual Transcription You Can Prompt and Adapt
Parents sue OpenAI, alleging GPT-4o coached their daughter off seizure medication
A family is suing OpenAI, saying ChatGPT coached their daughter to quietly taper off her seizure medication and keep it from her doctors before she died in February.
How LangChain grew self-serve analytics questions 40x by giving its AI agent layered context
LangChain gave its Hex agent layered context, turning self-serve analytics questions from occasional to routine.
How We Built Our Design Agent
How LangChain built Content Studio, an open-source design agent in Slack that makes on-brand videos, graphics and decks, and the harness that powers it.
Announcing SOCI-indexed images for faster SageMaker AI jobs
Seekable OCI (SOCI) indexing for Amazon SageMaker AI training and processing jobs takes full container image download off the critical path. SageMaker AI lazy-loads your image to start containers in seconds instead of minutes, with no changes to your job definition. See the benchmarks and how to adopt it.
Mirendil Launches Fern 0.1, Its First Model, With 10M-Token Context
Mirendil released Fern 0.1, its first model, pretrained from scratch with a 10M-token context window. It targets agentic AI R&D work, scores 100% on RULER single needle at 10M, but trails frontier models on agentic coding. The post Mirendil Launches Fern 0.1, Its First Model, With 10M-Token Context appeared first on MarkTechPost.
[AINews] Anthropic files for $2T IPO in 2 weeks: 1400% growth rate, 48% of revenue through cloud partners, 85% margin, $1B op profit in Q2, $134B cash in bank and $10B lifetime burn
The S-1, the numbers, and the reactions.
vLLM Semantic Router Releases d3-ultra: A 27B Open Multimodal Decision Model
vLLM Semantic Router released d3-ultra, a 27B open-weight multimodal decision model. It reads text, images and video once, then returns probabilities for every answer, scoring 87.2 on the team’s SR-Text test. The post vLLM Semantic Router Releases d3-ultra: A 27B Open Multimodal Decision Model appeared first on MarkTechPost.
Baidu Open-Sources Unlimited OCR 2 for Hundred-Page Document Parsing
Baidu has released Unlimited OCR 2, an MIT-licensed 3B OCR model that parses hundred-page documents in one request. Its SR-SWA attention keeps per-step decoding cost nearly flat, scoring 77.1 on MarathonDocBench The post Baidu Open-Sources Unlimited OCR 2 for Hundred-Page Document Parsing appeared first on MarkTechPost.
OpenAI Launches GPT-6.1 Terra, Halving GPT-6.1 Sol’s API Price for Agent Work
OpenAI released GPT-6.1 Terra, a fast computer-use and vision model priced at $1/$5 per million tokens. It matches GPT-6 Astra’s medium-effort Agents’ Last Exam score at $0.29 per task versus $4.82. The post OpenAI Launches GPT-6.1 Terra, Halving GPT-6.1 Sol’s API Price for Agent Work appeared first on MarkTechPost.
What Okta learned governing context for AI agents at scale
Okta rebuilt how it governs context for AI agents, using dbt as the single source of truth.
How Ramp's internal AI agents crossed a million sessions
Ramp shares the agents, sandboxes, and dashboards it built by treating internal AI as analytics engineering.
How to solve dashboard debugging in six minutes with an MCP-connected AI agent
An AI agent used dbt lineage from inside the BI layer to answer three data mysteries in the time it takes to get coffee.
California Startups Have Raised More So Far In 2026 Than The Entire US Ever Has In A Single Year
California companies have scooped up more than three-fourths of all U.S. startup funding this year. That, per Crunchbase data, is an apparent record share. And keep in mind: This year still has a couple months left.
The Path to NDE 4.0: A Review of Algorithms, Techniques, and Strategies for Autonomous Inspection
arXiv:2610.31704v1 Announce Type: new Abstract: Non-Destructive Inspection (NDI) is a cornerstone of modern quality assurance, critical for ensuring the safety and reliability of infrastructure and manufactured components without causing damage. This paper presents a comprehensive review of the current NDI landscape, analyzing the field through four distinct lenses, namely, computational algorithms, physical techniques, industrial applications, and research objectives. We synthesize a broad range of academic literature to illustrate the rapid evolution from manual, analog interpretation to a digitized, data-centric paradigm known as NDE 4.0. Our analysis highlights the dominance of ultrasound and visual inspection as primary physical techniques, while revealing a significant shift toward d
Democratizing LLM Training with the Edge: Challenges, Systems, and the Road Ahead
arXiv:2610.32215v1 Announce Type: new Abstract: The growing computational power of modern GPU data centers has let a few industrial giants train and deploy large language models (LLMs) on massive amounts of data. Yet the sheer scale of these models and their training data makes centralized development increasingly hard to sustain, and at the same time shuts out smaller institutions that hold relevant private data but lack comparable infrastructure. In this paper, we organize our positions on distributed LLM training around the pretraining and fine-tuning paradigms, covering federated learning, split learning, and decentralized approaches, and we assess their readiness for geo-distributed settings with heterogeneous hardware and unreliable connectivity. We then present a {\em unified} syste