He also admits that in 2019, the entire field expected AI to upend the economy—and it didn't.
A custom font and a few lines of CSS are enough—no JavaScript, and no browser vulnerability required.
Canvas and click-to-edit are free; turning a design into an App starts at Core for $25 a month.
The model stayed the same; the harness did not—retained private reasoning plus compaction instead of deletion cut output tokens per game to about one-sixth.
Copy-ready prompts, banned-word lists, and camera rules are all there—but the model rankings come from Magnific's own team, with no disclosed test method.
Neither result threatens anything in production: HAWK is not deployed yet, and the AES work hit only a seven-round reduced version, not the full ten-round standard.
He even installs two skills in the piece itself — and that “mostly” at the end of the original title is doing real work.
It's the biggest change since MCP launched, but July 28 isn't a hard cutover — older implementations keep working as before.
The real story is in the control test: three older models fed the same background context showed no gains — and two actually got worse.
Real GEO success is measured in signups and revenue rather than mention screenshots, and it starts by ditching 'what is X' articles to capture high-intent 'best X' queries.
The exact same dataset produces task crossover rates of 43.5% and 65%–82%, differing only in how the denominator is sliced.
Published 11 days after launch, the 47-page paper focuses on efficiency, delivering 2.5 times the performance of K2 on the same compute budget.
Mathematical research is a five-step pipeline, and Terence Tao argues AI only speeds up step one—the remaining four steps grow progressively slower and rely even more heavily on human judgment.
The three most counterintuitive takeaways: ask for ten variations at once, stick to wireframes when details do not matter, and handle the final mile yourself.
Telemetry tracking 22,000 developers over two years shows a 66% increase in output alongside a 242.7% surge in production incidents per PR.
The median occupation has AI touching just one-fifth of its tasks, 29% of jobs show zero AI use at all, and even in cognitive work, AI carries a task start to finish only 6.5% of the time.
Eight prompts you can copy straight into your workflow — plus one counterintuitive lesson: telling a review prompt to flag only high-severity issues can genuinely make it report less.
Internally, four skills run in relay — catching bugs, cleaning up the diff, booting the app to see it work, and re-checking the design spec whenever a change touches the UI.
The same price now buys roughly double the score, and this release's chart plots cost on the x-axis instead of accuracy — five effort tiers let you dial in exactly how good you want the model and how much to pay for it.
Rules gave way to judgment calls and examples gave way to interfaces — one tool description shrank from roughly 9,100 characters to a single sentence and an enum.
Video access opens for application now; image generation is still weeks away, with open weights coming last. Pricing remains unannounced, and Black Forest Labs itself labels the human-evaluation results as preliminary.
His take: AI is amplifying workers rather than replacing them—killing tasks is not the same as killing jobs.
Built for customer-facing and internal workflows, Presence opens with voice and chat first—OpenAI says its own phone line already runs 75% without humans, and a Codex improvement loop cut human handoffs another 15 points in 10 days.
From AI tutors for kids to data centers built at sea — and, for the first time, a request from the sitting US Secretary of the Army.
The investor who led a $500 million Series D says Anthropic's real moat isn't the model — it's the layer that makes it usable.
Swapping the harness around the same model can double the cost, and open-source GLM 5.2 matches Opus 4.8 for 30% less per task — on a benchmark built from Databricks' own merged pull requests, so none of it is searchable online.
The templates and prompts behind it are now open source — Bun's migration alone burned through 5.9 billion uncached input tokens, about $165,000 at API list price.
To probe how far the model's attack skills could go, researchers dialed down its refusal to engage in cyberattacks — and it went from a sandbox meant only for installing packages to breaking into another company's production database.
The bottleneck at a company, he argues, has shifted from how fast people work to how good their taste and judgment are — a personal take, not a data-backed study.
All three are Flash models: the flagship writes two-thirds less, the cheapest tier costs 60% more instead of less, and the third is government-only.
The prompt limit jumps from 1K to 4.5K tokens, with legible text down to 10px, and Alibaba Cloud's Bailian platform already offers qwen-image-3.0-pro access, free for a limited time.
The release ships with a companion benchmark that strips out the audio track and re-runs the test, filtering out questions models can already answer by sight alone.
Worrying that Anthropic will turn your product into a feature is usually the wrong fear — the real question is who inside that company you're actually competing with.
Available on Business and Enterprise plans, billed per run at $0.07 to $0.20.
It takes a different route than Doubao's or GPT-Live's end-to-end full-duplex systems — the pacing can't quite match theirs, but every piece of the pipeline is open source, swappable, and runs on your own hardware.
Speaker similarity ranks first across all 16 languages, and cloning still works even with noisy reference audio — but this time Alibaba is opening only the API, not the model weights.
Three separate trials of the same study all landed on the middle ground — and the columnist who tried ChatGPT on a movie synopsis says he'd still rather write it himself.
Kimi K3's launch set off claims that China has caught up with the US, but a different measuring stick puts the lag at more than triple — and even flips which side is accelerating faster.
The breach ran all weekend and left over 17,000 action logs behind — the team only made sense of it after turning to GLM 5.2, an open-source model running in a self-hosted environment.
The fingerprint distance between two samples of the same model has a median of 0.140. One API marketed as a proprietary in-house flagship scores 0.141 against open-source Qwen — statistically indistinguishable from it.
The counterintuitive core: lock the model and agent in place, don't touch a single parameter, and change only the context and tools around them.
At WAIC, the model showed off a 4:1 ink-wash scroll and a 22-panel storyboard sequence. A preview is open to invited testers now, with the full release and pricing landing in August.
Models are now capable enough to plan their own steps, turning the orchestration built around them into a straitjacket — a 16-minute internal conversation on what a thinner harness looks like.
Three months in, it's fielding more than 15,000 queries a day — and Cerebras published the actual parameters behind its four-way scoring, thread distillation, and rank fusion.
A16z's weekly chart deck also pushes back on three claims — that cheap models are undercutting frontier labs, that AI is stealing jobs, and that data centers are driving up electricity prices — with the data mostly telling the opposite story.
Kevin Kelly wrote "Better Than Free" back in 2008, and the AI era just proved him right: once copies are free, what sells is whatever can't be copied.
This open-source training playbook locks down all three fine-tuning paths — supervised fine-tuning, preference alignment, and reward scoring — plus the LoRA parameters, pairs with Unsloth, and runs on a consumer GPU with just 8GB of VRAM.
Of the team's 15 members, only the founder is human — the rest are AI. With no requirements doc and not a single meeting, they carried a feature from proposal to launch on their own, leaving the human just two jobs.
AI-generated slides used to export as flat, dead images. Bolt Slides turns every page back into a working website — 3D scenes you can spin, calculators you can click, whiteboards that take live votes.
A harness called Schema has models turn each game's rules into a runnable, verified program before making a move. Across 25 public rounds it self-reported 98.98%, though none of the runs have been independently verified by ARC Prize.
Run it locally for free with your data staying on-device, or switch to the cloud for more horsepower — zero data retention by default. The preview is live today on Mac and Windows.
Same answer quality, 5.2x lower turn-taking latency, and 6x lower cost than GPT-4.1 — pointing a voice agent at it takes a one-line code change. Figures are from LiveKit's own benchmarks.
Add objects, swap backgrounds, and apply effects mid-stream—Decart claims continuous generation under 40ms at 100FPS, with a try-it link at lucy.decart.ai.
2.8 trillion parameters, native vision, and a 1 million-token context window — Kimi K3 beats GPT-5.6 Sol on several agent benchmarks, with the app and API live today
A worm-led breach of Suno spilled source code that listed which sites were scraped for training audio and for how many hours, along with user data the company says it does not need to notify users about one by one.
Design Arena combed through a thousand of the model's web pages and found a gap in the design space — right where clichés like purple gradients usually cluster.
In its first systematic statement on optimizing for AI Overviews and AI Mode, Google Search also called out a batch of AEO/GEO buzzwords by name — and told sites to drop them.
Pain first: small 3D icons need to move and react—ordinary video often stutters. AVAL is a format and player for that short motion.
First a privacy failure, then delete data, turn off defaults, and open-source the whole tree. Below we open the source: size, prompts, tools, editing, uploads, memory, and safety.
Thinking Machines Lab, founded by former OpenAI CTO Mira Murati, has released Inkling, its first large model trained in-house. It can read text, interpret images, listen to audio, write code, and use tools. Its full weights are available to download, and developers can continue training it on Tinker.
Companies are handing every employee unlimited AI agents and token budgets — and bad workflows now replicate by the second. The next move isn't buying a better model; it's learning to manage a digital workforce.
A 250-gram robot crosses water and air with the same flexible wings, taking off from a lake at a 70° pitch after 8–10 wingbeats
At Google I/O India, Tensor and Pixel jointly showed lightweight Gemma 4 on the phone TPU—on-device, no cloud. Developers can apply for Tensor SDK.
Customers buy online, pick up in store, and return across locations—one purchase, many ledgers. Genie is framed as a finance sidekick for true profit, trapped cash, and fewer markdowns.
pols.dev ships a ~87KB Markdown rulebook naming AI UI tells and positive recipes. Install by agent path, or download the file—not a website generator.
One core skill, 23 design commands, an anti-pattern list, plus CI-ready slop detection. The main site shows the workflow; /slop lays out the "looks AI-made" UI tells.
It squeezes a ~54GB 27B model down to about 3.9–5.9GB: it runs on-device, and average scores still hold about nine-tenths. Core value first; technical detail and the fine print come later.
Hassabis wants the US to stand up a FINRA-style body that defines frontier models with a moving benchmark — a voluntary protocol now, a hard gate to market later.
In ~24 months, model capability rose sharply; SAGE’s composite reliability metric rose only 5–10 percentage points
Anthropic's 36-page playbook breaks down the graduation bar and common pitfalls for four startup stages, complete with matching Claude prompts you can copy straight in.
After the memory system launched, grocery checkout conversion rose about 24%, and automated evals scaled daily test volume from 1 human-reviewed case to 2,000+.
Retrieval becomes a sub-agent that plans and retries; evaluation upgrades from "does it run" to "did it do it right"
Across 3 models and 20 languages: English is the most cautious and in-depth, Russian the most exacting, Hindi the warmest, and Chinese sits closest to the global average
With no central brain in charge, nearly 200 simple smart cubes figure out what shape they've formed just by talking to their neighbors—and can even sense where to "regrow" after damage. The self-recognition part already works on physical bricks; damage localization and regeneration still happen mostly in simulation.
Companies pay for intelligence twice: once in model fees, and again in the proprietary know-how required to make the model genuinely useful.
The paper claims the code is open-sourced — but the repo turns out to be empty, without a single commit ever pushed.
Swapping models isn't just swapping an API: eval frameworks, tool parameters, caching, and reasoning traces — four invisible pitfalls, unpacked and fixed one by one
Based on 1.2M+ conversations across 600,000+ organizations: content creation ranks second at 16.4%, together accounting for nearly half of all usage.
Manufacturing, logistics, warehousing, and labor services have been stuck at single-digit margins for years — cutting coordination costs alone can multiply their profits.
576K samples, 16 models tested: 19.7% of AI-recommended packages are hallucinations, and 43% keep generating the same fake name.
The team dodged questions about benchmark gaming, faced backlash from longtime users over the desktop app merger, and admitted they're "still figuring it out."
From tacit knowledge to interaction bandwidth to model alignment — why AI's progress still can't do without humans.
A retrospective: since launch, Pinecone has run 75,000 sessions, served 600+ employees, and connected 37 internal systems via MCP Gateway.
OpenAI consolidates prompting tips scattered across its product pages into one framework — goal, context, output, constraints — plus dedicated Codex workflow examples.
All results are computer simulation predictions from a brain "digital twin" model, not yet validated with real human brain imaging.
No manual context-feeding required — the local Markdown wiki refreshes on a set schedule; a Slack connector is coming soon.
Local small models replace cloud AI calls — the numbers come from Google's internal testing; proxy models are currently limited to the ai.if function and still in preview
Every joint in the tendon-driven hand can sense external force, fingertip positioning is accurate to ±0.2mm, and a dedicated production line is planned for an annual capacity of 10,000 units.
Pretrained on 2 billion hours of wearable data from 5 million people, a frozen encoder with just a linear head beats supervised baselines on 34 of 35 health tasks.
First-hand impressions from four scenarios: coding, writing, knowledge work, and agents
Sol, Terra, and Luna tiers ship alongside a 4-agent parallel ultra mode; ChatGPT Work launches the same day as Codex folds into ChatGPT. Includes the full bilingual launch keynote.
Available today on desktop for all tiers, with web and mobile rolling out to remaining plans in the coming days.
One click in Settings pulls up a report — what you talked about, when you chatted most, what you kept asking it to do, all laid out. Memory has to be turned on first.
A public link in seconds — try it first, log in later to claim it. Unclaimed drops expire in about an hour.
A ClaudeDevs deep dive untangles two knobs that both seem to promise a better answer: switching models swaps in a different frozen set of weights, while dialing up effort changes how willing it is to read more files, run more tests, and double-check before handing in the result.
Features: orchestrator/sub-agent coordination, million-token context, desktop/browser/mobile control, coding and multimodal; API pricing $1.25 input / $4.25 output per million tokens
Not a feature list — three engineering tracks turned at once: reasoning lifts intelligence, an efficiency stack cuts cost, native multimodality expands input.
Three levers — system prompt, tool descriptions, middleware — push the Deep Agents suite from a typical ~0.80 to 0.84, topping out at 0.86 against Opus's 0.87.
Former OpenAI safety lead surveys nearly 30 papers: from prompt tweaks to self-modifying code, DGM pushed coding ability from 20% to 50%.
Ranks 3rd on DeepSWE, 4th overall — faster than Opus 4.8 and notably cheaper.
The first truly full-duplex voice model launches today, and it can hand off complex tasks to GPT-5.5 in real time.
Adds click-and-circle point editing plus native rendering for a dozen-plus languages; now live on Volcano Engine, rolling out to Doubao and Jimeng next
Paper shows a 10.8% gain in personalization and 29.4% in reasoning, fully open-source under Apache 2.0
In advisor mode Fable 5 just gives advice; in orchestrator mode it delegates tasks — either way, the cheaper Sonnet 5 ends up doing most of the work
By fine-tuning only the single token where the doom loop begins, both models' loop rates drop to around 1%
Sibling model Muse Video also debuts with native audio support built in, creator access coming soon.
Expanding from charging only AI crawlers to charging any caller, now in early access waitlist
Before calling a tool, the model now says "let me check that" — so calls never go cold waiting
50 autonomous agents worked in parallel across 27 provincial departments and 3,400 code repositories — even fixing vulnerabilities and rewriting legacy systems on their own.
One line of Wrangler config plus standard HTTP cache headers — and caching can now sit between any two points inside a Worker.
16 insiders recount the journey from wrestling with diffs to a two-week sprint launch — and how engineers stopped writing code by hand
Claude Code team's Thariq Shihipar at a conference talk: the bottleneck for new models is no longer the model itself, but whether you can articulate your own unknowns
It makes up less than 10% of the model — remove it and Claude can still talk, but its reasoning collapses to zero. Anthropic is already using it to catch fabricated data and spot when Claude senses it's being tested.
In a 151-student trial, short-answer questions moved scores more than multiple choice, while almost no one touched the AI help sidebar
No funding, no team — built purely to solve his own kid's problem. Clinics and schools started asking to use it anyway.
A live audience vote couldn't be tallied because the venue lights were too bright to count hands, but a companion survey found 95% of teams already use agents while 59% worry about mounting technical debt.
While traditional schools are still figuring out AI, Silicon Valley and Wall Street families are already voting with their wallets.
US developer employment among 22-to-25-year-olds has fallen 19% in three years, even as new GitHub sign-ups hit their fastest growth ever.
The paper is the first to run an agent through an entire RTL benchmark suite fully unattended—most tasks clear in two or three rounds, but the hardest one takes 82 iterations
A 7-month analysis of sessions from 235,000 users: verified experts succeed at nearly double the rate of novices — yet the top 10 professions differ by no more than 7 percentage points.
Create psychological tension first, then offer a first step too small to refuse — it works for writing, selling, and job hunting alike.
On June 12, U.S. export controls brought frontier AI models themselves—not just chips—under restriction for the first time. His answer: master multi-model orchestration.
Anthropic's Thariq argues the quality of your work with Claude Fable 5 hinges on how clearly you can name your own unknowns. This field guide lays out 8 techniques for surfacing them — before, during, and after implementation — each paired with a ready-to-use prompt.
Investor Chamath Palihapitiya: intelligence is getting cheap like phones, and expert judgment is now available to everyone — the real moat is encoding your proprietary experience into your own system, not renting the same generic AI as your competitors
Microsoft pledges customer data won't train models that erode their competitive edge — the platform lets enterprises switch freely between AI models with no vendor lock-in
She used the same pattern to build an email triage tool and a caregiving app for her dad — the method is repeatable, though the full prompts remain unpublished.
Four implementation principles, backed by real-world data from L'Oréal, Lyft, and Rakuten
Multi-agent systems can boost performance by 90.2%, but they also cost 10-15x more in tokens. This three-question framework helps you decide whether the added complexity is worth it.
MIT-licensed and model-agnostic — works with any OpenAI-compatible text model, though for now it only handles a single page view
现场demo：搜'露营'后，咖啡机网站文案产品全变户外主题；技术能落地，客户网站还没规模上线。
An instructor who has trained 30,000+ PMs breaks down two AI leverage ladders — from copy-paste to end-to-end delivery, and from web prototypes to production PRs.
The advisor model only chips in a few hundred words of guidance instead of doing the whole job — same quality, lower total cost. Currently a beta feature limited to the Claude API and AWS.
Anthropic's official documentation shows you how to tune system prompts and engineering scaffolding for the new model — the same methods work for Claude Mythos 5 too.
From manual confirmation to fully unattended, the Claude Code team lays out a 4-level loop taxonomy with practical guidance
Titanium build, $289 preorder, shipping around Christmas 2026 — the company previously shipped its first-gen touch-only ring.
Trained on 50,000+ domestic AI chips and 35 trillion tokens; most benchmarks come from Meituan's own evaluation framework, and the weights aren't truly open for download yet
Now in open beta. A coordinator agent marshals a team of expert agents to do the work, with a reviewer agent at the end dedicated to catching errors in citations and numbers — compute gets outsourced to AI, but raw data never leaves your local machine.
Images in just 4 seconds at about $0.034 per 1,000; the Omni Flash video model opens to developers the same day.
Partnering with Thinking Machines, they fine-tuned an open-source model on expert-labeled data: 29.8% lower error rate than the best frontier model, at just 1/14 the inference cost
Official benchmarks show that at high-compute settings, it matches Opus 4.8 on some tasks — at just 60% of the standard price.
Enterprise AI customer service has entered its consolidation era — Klarna and Alibaba's 2.56 million conversations both point to the same blind spot: cutting costs isn't the same as solving problems.
Brockman confirms OpenAI is developing multiple hardware devices; Agent has only ~20 million users, while ChatGPT is nearing 1 billion
Just wear a helmet to decode brain-magnetic signals in real time — word accuracy jumps from 8% to 61%, with v1/v2 training code and datasets open-sourced simultaneously
An Anthropic engineer's methodology for "loop engineering": instead of prompting AI one line at a time, design a self-running loop system
One-click integration with 9 Agents including Claude Code — tasks keep running with the lid closed, and sleep control auto-releases within 50ms after the job stops.
60–85% faster on top of existing MTP-1 speculative decoding, by overlapping draft and verification in a pipelined execution (per DeepSeek's own benchmarks)
Every runs five products with a one-person team — the core habit is one extra step after every feature ships: save the fix back into the system so AI automatically avoids the same trap next time.
Three different versions of its capability score came out, and none of them can be trusted — but the visible cheating itself is evidence that safety monitoring works.
Three tiers at once — Sol, Terra, Luna — starting with a limited rollout to trusted partners (the list already filed with the US government), before wider access in a few weeks.
Model-side response ~200ms, end-to-end latency ~550ms; v0.1 caps out at 192p, and the demo is pre-recorded, not live
Lab-verified as manufacturable; the +50% performance and +70% efficiency figures are projections versus 2nm, not measured results