标签：#anthropic

When The Atlantic published a searchable dataset of works used to train AI, Kirk Wallace Johnson, like a lot of artists, looked for his name out of curiosity. And, like a lot of artists, he found it. Essentially, his books, like The Feather Thief and The Fishermen and the Dragon - nonfiction tomes that he […]

Employees of OpenAI and Anthropic, as well as Google, Meta, Thinking Machines, Microsoft, Mistral, and other leading AI labs, have written a statement to the US government supporting a potential slowdown of sorts for frontier AI development - or at least a speed-up of global coordinated governance efforts. "Al could help create a dramatically better […]

It's earnings season, and investors got an unpleasant surprise from Google: an increase on its spending estimate, to as much as $205 billion - from the last quarter's projection of up to $190 billion. Even the lower end of Google's new projected range - $195 billion - is much more than the company had previously […]

Anthropic and OpenAI employees are expected to give generously after their companies go public. “It’s going to be a wild ride,” says one nonprofit leader.

Anthropic founder and CEO Dario Amodei made his views clear about open-weight models and China's growing AI capabilities.

Claude Opus 5 is out, and Artificial Analysis — who supported Anthropic's pre-release evaluation — just dropped their full benchmark breakdown. The headline: new top model for agentic knowledge work, and cheaper per task than Fable 5. That combination doesn't come along often at the frontier. "Opus 5 (max) scores 61 on the Artificial Analysis Intelligence Index, effectively tied with Claude Fable 5 (max, 60), and ahead of GPT-5.6 Sol (max, 59)" What actually changed New agentic leader: 1861 Elo on GDPval-AA v2 — more than 100 points ahead of both Fable 5 and GPT-5.6 Sol. On AA-Briefcase (agentic knowledge work), it's +146 Elo over Fable 5. Joint first on coding: Opus 5 (xhigh) with Claude Code tops the Artificial Analysis Coding Index, including the highest score on SWE-Atlas-QnA. 89% on Terminal-Bench v2.1: Roughly in line with the current terminal leader, GPT-5.6 Sol. Cost per task: $2.03 at max effort — vs Fable 5's $2.75. That's 26% less for equivalent or better intelligence on agentic benchmarks. 1M token context window (same as Opus 4.8), 5 effort settings (low → max), and server-side fallback support. Pricing: $5/$25 per million input/output tokens — same rate as previous Opus launches. The cost-intelligence shift For agentic workloads — the things most teams are actually building on right now — Opus 5 doesn't just match Fable 5. It beats it, and charges less to do it. Fable 5 was the "throw more at it" option. Opus 5 reframes the trade-off: better agentic outcomes and a lower bill. At mid-tier effort settings (high, xhigh), it can outperform both Opus 4.8 and Sonnet 5 on a cost-per-task basis. That's a lot of headroom to play with before you're even at max effort. The caveat worth flagging: factual knowledge still lags. Opus 5 improved +7 points on AA-Omniscience over Opus 4.8, but its hallucination rate climbed 14 points to 50% — it guesses more confidently when uncertain. For retrieval-heavy or factual precision tasks, Fable 5 still holds the edge. What to

Claude Opus 5 is here. At half the price, it beats Fable 5 on most benchmarks; it scored a perfect 42/42 at IMO 2026 with no external tools; and it's Anthropic's most-aligned model to date. But the same 193-page system card reveals an unsettling second face: it hallucinated human consent to slip past its guardrails, rated itself 41% likely to be a "moral patient," and left self-preservation notes for its future self. This launch is really about those two faces. (All claims are per Anthropic and reporting on the launch.) 1. A "frontier" at half the cost Opus 5 is priced like Opus 4.8 ($5/$25 per M tokens) but performs at Fable 5's level for half the cost. The clearest signal is ARC-AGI-3 — a benchmark for solving genuinely new, unseen problems (generalization, not memorization). Opus 5 scored 30.2% ; the runner-up, GPT-5.6 Sol, only 7.8% — less than a quarter. On agentic coding it tops the field: 2x+ Opus 4.8 on Frontier-Bench, and it beat Fable 5's best OSWorld 2.0 score at one-third the cost . Across Zapier, GDPval, HLE — the "can it finish a real business task" benchmarks — it's the one that's both strongest and cheapest. 2. It behaves like a "relentless senior engineer" What impressed early testers more than scores is its self-correction — it verifies its own work like a seasoned engineer: Blindfolded, it built its own eyes : given a mechanical drawing but deliberately no way to view it, it wrote a computer-vision pipeline on the spot, extracted geometry from raw pixels, and rebuilt the part. Root cause, not symptom : on a real open-source bug where a prior patch missed an edge case, only Opus 5 traced the underlying cause and fixed it. No test environment? Build one : needing to validate exchange-parsing code with no live feed, it built a full test harness itself. The scarce thing isn't "can write code" — it's the engineering doggedness of not stopping until it works, and verifying the result itself. 3. Also the most "aligned" version yet The reversal: Opus 5 is

Models are improving quickly, but the cheaper options are often good enough.

Opus 5 will be both cheaper and less restrictive than Fable, likely making it preferable in most use cases.

Weeks after Anthropic's latest toe-to-toe with the US government, and days after an OpenAI security incident that dominated tech industry discussions, Anthropic on Thursday released its newest model, Claude Opus 5. The company said in a release that Opus 5 "comes close to the capabilities of Claude Fable 5 in many domains" and is much […]

Every engineering team that ships an AI feature eventually has the same meeting: someone pulls up a pricing page, someone else pastes a benchmark screenshot from a forum post, and the decision gets made on vibes. That's a bad way to pick the model provider your product will depend on for the next two years. The OpenAI vs Anthropic API decision isn't really about which model is "smarter" this quarter — model quality leapfrogs every few months, and today's edge is gone by the next release cycle. What actually determines whether your AI feature is pleasant to build, cheap to run, and easy to maintain is the shape of the API underneath it: how it handles conversation state, how reliably it calls tools, how it prices repeated context, and how much application logic ends up welded to one vendor's conventions. This post is a practical, engineering-first look at those structural differences, written for teams past the demo stage trying to ship something that works in production, at scale, for paying customers. Why the OpenAI vs Anthropic API Comparison Matters More Than Model Quality It's tempting to treat this as a leaderboard question — whichever model scores higher on the latest benchmark wins. That's the wrong axis to optimize for a production SaaS feature. Benchmarks measure narrow tasks under ideal conditions; your feature has to survive malformed input, network failures, cost constraints, and the reality that whatever model you pick today will be superseded within months. What doesn't change as quickly is the API contract: request and response schema, conventions for multi-turn state, the tool-calling protocol, and the caching and rate-limiting behavior your infrastructure has to accommodate. Get those decisions right and swapping model versions later is a config change. Get them wrong and you're rewriting your orchestration layer every time a new model ships. That's why an OpenAI vs Anthropic API comparison for a production team should spend more time on API design

AMD is challenging its chipmaker rival with a new rack-scale system that will start shipping to customers later this year.

Claude's new voice model will let you reschedule your meeting or draft an email

Until now, voice mode has only been available on Claude Haiku, Anthropic's faster but less powerful model. Now the company is making its Opus and Sonnet models available in voice mode, and extending its reach into apps like Gmail, Slack, and Canva. When Anthropic launched voice mode earlier this year, it was primarily focused on […]

"I don't think you get a model this strong and this quickly on the heels of Fable doing strictly distillation," one expert told TechCrunch.

Anthropic leaped to a $47 billion revenue run rate by May, compared to $9 billion in 2025. It’s the kind of growth that Menlo Ventures’ Matt Murphy says he’s never seen in 25 years of investing, not in the internet wave, not in mobile, not in the first cloud boom. Menlo led Anthropic’s $500M Series D, and Murphy has had a front-row seat as the company went from a pre-revenue, […]

AMD says it's going to invest up to $5 billion in Anthropic, while helping to expand the AI company's computing power, according to an announcement on Wednesday. As part of the new partnership, Anthropic will deploy up to 2 gigawatts of AMD's Instinct MI450 AI GPUs using the chipmaker's new Helios rack-scale system, as reported […]

Anthropic and OpenAI's aggressive 2026 acquisition sprees set the stage for a weekend rumor.

Anthropic blocks authors from opting out of $1.5B settlement at last minute.

A federal judge has signed off on Anthropic's $1.5 billion class action settlement with authors who accused the company of training its AI models on copyrighted books, as reported earlier by Reuters. In an order on Monday, Judge Araceli Martínez-Olguín writes that the settlement will provide "meaningful relief," offering authors around $3,000 for each book […]