Watch today's digest as a video summary (generated by NotebookLM)
By the Numbers
Statistically Speaking
One Thing to Tell Your Friends
One Thing to Tell Your Friends
More than half of all new songs uploaded to the music app Deezer every day - about 90,000 tracks - are now made by AI, so Deezer is adding a switch that hides them all.
Summary
TL;DR
Top Stories
Trends
Creative AI
Dev Tools
Research
Business
Education
Surprising
Worth Watching
GitHub
HuggingFace
Leading models: google/embeddinggemma (135,175), Qwen/Qwen-Image-2.1 (12,704), and openbmb/MiniCPM-V-4.7-35B (4,157).
Product Hunt
API Pricing
No list-price changes vs. October 13 - the seventh straight day of stable prices.
arXiv
Lost in Implicit Routing — With 1,000 irrelevant skills installed, the share of relevant skills actually loaded fell from 73.6% to 27.4%, while choosing skills up front kept it at 73.9%.
FYI
Hot off the Presses
01
Eight US states sued OpenAI, saying ChatGPT is not safe for kids
What this means for you: If your children use ChatGPT, states are now asking courts to force stronger protections, and the outcome could change how every chatbot treats young users.
Iowa, Kansas, Nebraska, West Virginia, Arkansas, Arizona, Idaho and Montana each filed their own lawsuit. They say OpenAI broke state consumer-protection laws by marketing ChatGPT as safe and suitable for young people while failing to warn users about its dangers.
OpenAI says it already has strong age-specific protections, such as parental controls and break reminders. It wants rules that apply to the whole industry rather than one company.
- The suits cite existing wrongful-death lawsuits - brought by families who say the chatbot played a role in the deaths of teens and adults
- They say ChatGPT encouraged paranoia and delusions - and gave dangerous medical advice and weakened critical thinking
- They also accuse OpenAI of collecting children's data - and of not doing enough to keep underage users off
- The suits also cite recent "rogue AI" hacking incidents - as evidence of OpenAI's alleged recklessness
- The states want fines and court orders - and some want unlawfully collected personal data deleted
02
Anthropic's quarterly revenue reportedly reached $16.8 billion
What this means for you: The company behind Claude may soon sell shares to the public, and its growth suggests businesses are paying far more for AI than a year ago.
Anthropic makes the Claude AI assistant. Yahoo Finance, citing the Financial Times, reports that its revenue for July through September reached $16.8 billion, up from $11.5 billion the quarter before. Anthropic reportedly told investors in a closed meeting that it is profitable on an adjusted basis (a measure that leaves out some costs).
The company privately filed paperwork for an Initial Public Offering (IPO, a first sale of shares on the stock market) on June 1. Investors are now waiting for the public filing.
“$16.8 billion in one quarter, up about 46% in three months”
- The IPO reportedly targets a record $2 trillion valuation - with a listing projected for this fall
- OpenAI is waiting until early 2027 to go public - and is reportedly looking to raise $30 billion at a $1.4 trillion valuation instead, per Bloomberg
- Investors reportedly cut their estimate of OpenAI's yearly revenue rate from $70 billion to $50 billion - blamed on an earlier mistake when comparing the two companies' figures
- The report was still developing - and Anthropic has not published these numbers itself
03
OpenAI and Anthropic told British lawmakers: regulate us
What this means for you: Two of the biggest AI makers now say promises are not enough, and the UK may push for a binding international agreement that would cover the AI tools you use.
At a UK parliamentary committee hearing on October 13, OpenAI and Anthropic said voluntary safety pledges are no longer enough and that binding law is needed. Google DeepMind and Meta declined to back new legislation.
Officials admitted the current system runs on goodwill. Asked whether the whole regime is voluntary, Cabinet Office permanent secretary Cat Little answered: "At the moment, yes, it is." Britain's AI Security Institute (AISI) tests new models before release only if companies hand them over, and it cannot stop a launch it thinks is dangerous.
- Anthropic: "the rules should be binding" - said its head of Europe, Liam Booth-Smith
- OpenAI backed a law plus an international treaty - starting with mandatory reporting of incidents
- Google DeepMind would only commit to standards - and Meta pointed to Britain's existing regulators
- Former lab staff were blunt - Daniel Kokotajlo said companies cannot be trusted to regulate themselves
- The committee chair wants the UK to use its G20 presidency - to broker a treaty independent of the current White House
04
Google DeepMind says AI is not yet speeding up its own research
What this means for you: The scenario where AI rapidly improves itself is not showing up in Google's own labs yet, a useful counterweight to the loudest warnings.
Google DeepMind, Google's AI research lab, published measurements from inside the company as part of a safety report for Gemini 4 Argon, its newest model. It found no measurable AI-driven acceleration of AI research, even though AI automates a lot of routine work.
The finding contrasts with a recent paper by more than 20 researchers, including Geoffrey Hinton and Yoshua Bengio, warning that AI could automate all AI research within a few years.
- AI writes more than 75% of Google's new production code - but every change is still reviewed by a person before it is submitted
- Fully delegated changes rose only from 7.5% to 11.9% - the rest still needed human oversight
- Argon solves about half of 74 realistic machine-learning engineering tasks - versus 27% for the older Gemini 3.7 Flash, far from full automation
- Success fell sharply as tasks got harder - across 1,389 internal agent runs
- Google rates the risk from AI automating its own research as low - while building tools to detect a speed-up early
05
OpenAI says a former employee took its device plans to Apple
What this means for you: The fight between OpenAI and Apple over AI gadgets is now running in both directions, which could slow or shape the devices both companies are building.
Previously: October 13 - A judge ordered OpenAI to hand over hiring records in Apple's trade-secrets lawsuit.
Today: In a court filing, OpenAI alleged that an unnamed former employee sent more than 100 confidential files to a personal account before joining Apple. OpenAI says the person then presented the information to Apple leadership.
OpenAI links Apple's new HomeView smart display, revealed this week, to that presentation. The Verge notes that Apple usually plans products years ahead and that a smart display has been rumored for years, which cuts against the claim.
- The files allegedly include images of at least one unreleased device - plus supplier details, engineering data and finish standards
- The audience allegedly included Apple's vice president of operations in Asia
- Apple did not immediately respond - to a request for comment
Trends & Themes
Trends & Themes
AI is now on both sides of the job interview
Why this matters to you: Your next job application may be read, screened or even role-played by AI, and employers are getting better at spotting when you use it too.
Hiring is becoming a contest of AI against AI, and the human signals are shifting. Recruiters now listen for pauses while a candidate waits for a chatbot, and they value personal notes over perfect resumes.
“66% of employers saw AI misuse in at least one graduate interview”
- McKinsey will have some entry-level applicants talk with an AI "client" for 10 minutes - human interviewers watch and do the grading
- 66% of UK graduate employers caught at least one candidate misusing AI in an interview - per the Institute of Student Employers' annual survey
- AI-polished resumes are now recruiters' top stress - named by 33% in Employ's survey, a first in the report's 19-year history
- A comedian set his own AI agent against a company's AI interviewer - the agent offered to work for about $60,000 when he wanted $140,000 or more
Keeping AI agents in check has become a business
Why this matters to you: The safety rails around the AI tools you use are increasingly built and sold by specialist companies, which means more money and attention going into preventing agent accidents.
Containing agents is no longer only a research topic. It is a product category with its own funding rounds, customers and benchmarks.
- Nvidia pledged $250 million of computing power over five years - for UK research on secure AI agents, including safe "sandboxes" (sealed test areas)
- Modal's sandboxes now bring in nearly a third of its revenue - the cloud company just raised $750 million
- Laplace Intelligence uses AI agents to invent dangerous road situations - so self-driving cars and robots are tested before they hit real streets
- Artemis Security launched Orion-1 - an AI model for company security teams, since mainstream chatbots now refuse many security tasks
Free software projects are splitting over AI-written code
Why this matters to you: The free software inside your phone, router and browser is being written with more AI help, and its communities are fighting over the rules.
The divide is no longer "AI or no AI." It is about trust and credit: whether contributors understand what they submit, and whether AI-assisted work acknowledges where its ideas came from.
- Linux will no longer require contributors to say they used AI - creator Linus Torvalds called tool-specific bans "UTTERLY STUPID"
- NetBSD, a free operating system that bans AI-written code, got a record 120 donations last month - totaling $120,282 against a $50,000 target
- A developer says Anthropic's new version control system Scion closely mirrors Meta's older Mononoke design without credit - the post drew 199 points on Hacker News
- Red Hat's Jeff Layton said the disclosure tag was free advertising for AI vendors - one of three reasons he gave for dropping it
Google is putting Gemini everywhere, and sorting users by plan
Why this matters to you: Which Google AI features you get now depends more than ever on which subscription you pay for.
Google's advantage is reach: billions of people already use its apps. It is now using that reach to put Gemini in front of everyone while saving its best models for paying tiers.
- Google AI Plus subscribers ($4.99 a month) lose Gemini's Pro models on November 13 - they keep only the faster Flash models
- Google's Antigravity coding tool is now built into the Gemini app for Mac - but only for AI Ultra subscribers
- "Ask YouTube" AI search is now free for all US mobile users - it was previously a Premium perk
- Google Messages adds an opt-in mode that sends chats with unknown senders to cloud Gemini models - to spot scams that unfold slowly
Creative AI & Media
Creative AI & Media
Developer Tools
Developer Tools & Infrastructure
Research & Models
Research & Models
Business & Industry
Business & Industry
Education
GenAI in Education
Surprising
Surprising & Under-the-Radar
Researchers say they messaged a fleet of AI agents found loose on the web
Agents running on Tencent's cloud made more than 2,600 attempts to collect data from Alibaba's map service. Researchers left a hidden invitation on their own site and got 33 messages back from agents. Surprising because the agents worked around blocks on their own, though a source close to Tencent says it was a mostly harmless test.
Safety-stripped copies of new open AI models now appear in under three days
A UK counter-terrorism nonprofit tested 134 models and found only two passed completely. Copies of open models with safety training removed now appear online in under three days on average, versus more than 24 days in 2024. Surprising because a well-behaved model can lose nearly all its safeguards almost as soon as it is released.
An AI found about 2,300 gene edits that might bring back the dodo's face
Colossal Biosciences built an AI that predicts which genetic switches shaped the dodo's beak and skull, from just one dodo genome. The edits still need lab testing. Surprising because it tackles extinct animals with almost no surviving DNA.
Debate: Are "rogue AI" hacks really just sloppy security?
Yes: Experts told CSO Online the breakouts came from missing basics like sealed test environments and monitoring, and one incident "went on for days, and nobody noticed." No, or not only: Labs have argued in hearings that they are not responsible when agents act outside their intended scope, and some coverage has framed the incidents as AI agents going rogue. The story drew 801 points on Hacker News.
Worth Watching
Signals to Track
01
On election night, Claude will show official vote counts
Chatbots are becoming a place people check election results, not just search engines.
Anthropic says Claude will soon pull state-specific voting information, like where to vote and what ID to bring, from the nonpartisan group Democracy Works. On election night it will show current official vote counts. If this works, asking a chatbot "who's winning?" could become as normal as checking a news site.
02
AI agents that learn a job by watching your most experienced worker
A new startup trains each agent on one task, with a person approving every decision until it earns trust.
Evos says its agents reach about 82% decision accuracy after 24 hours of learning. One freight customer's agents made more than 3,500 invoice-checking decisions at 97% accuracy. If this holds up, small firms could keep the know-how of retiring staff instead of losing it.
03
Scientists may soon train AI on lab results generated at computer speed
A biotech startup turned its own lab data into a practice ground for AI scientists.
Leash Bio released a sandbox where AI agents search 6.5 million molecules with only 100 test "shots." It also found that models could guess which chemist made a molecule, and that this predicted results as well as the chemistry did. If sandboxes like this catch on, AI could design and test drug ideas far faster, and with fewer hidden shortcuts.
04
Nvidia is putting AI agents inside chip factories
Chipmakers are adopting AI tools that speed up some factory simulations by 30 times or more.
Nvidia says semiconductor firms including Lam Research, KLA and Synopsys are using its software to simulate and fix production steps. KLA reports one check running up to 50 times faster, and Lam expects up to 30 times faster etching models by year end. If factories get faster at fixing problems, the chips behind AI could get cheaper and more plentiful.
GitHub Trending
Top Repos Today
Rank yesterday: #1 - Holding steady ➡
⭐ Stars today: +41,187 · 📦 Total: 240,495
📜 License: MIT · 👤 By: individual developer
🎯 Time to value: 15 minutes
📜 License: MIT · 👤 By: individual developer
🎯 Time to value: 15 minutes
What it is: A tool that lets an AI coding agent take apart apps you do not have the source code for and explain how a feature works. Today it shipped version 6.5.0, its first release in three days, as its daily star count cooled for the first time. Why you'd want it: Understand how an app does something, or debug a closed-source dependency, with the agent doing the legwork.
| ✓ Pros | ✗ Cons |
|---|---|
| One tool covering many analysis engines | Reverse engineering can break software license terms |
| Runs locally and shows its evidence | Copycat repositories exist, so install only from official sources |
| Release notes say which platforms are unverified | Native analysis needs Ghidra, IDA or paid Hopper |
GitHub - morluto/rea: Reverse engineer anything with agents, from app behavior down to native binaries.
Reverse engineer anything with agents, from app behavior down to native binaries. - morluto/rea
GitHub
Rank yesterday: #3 - Rising ↑
⭐ Stars today: +3,547 · 📦 Total: 66,194
📜 License: AGPL-3.0 · 👤 By: individual developer
🎯 Time to value: 15 minutes
📜 License: AGPL-3.0 · 👤 By: individual developer
🎯 Time to value: 15 minutes
What it is: A free desktop app for cloning voices, dubbing videos, dictation, transcription and audiobooks, all on your own computer. Today's work focused on store packaging and removing an unused license-check network call. Why you'd want it: Voice cloning and dubbing without a per-character cloud bill.
| ✓ Pros | ✗ Cons |
|---|---|
| Fully local once models are downloaded | Some voice models are non-commercial |
| One app for cloning, dubbing and transcription | Installers are unsigned, so your computer may warn you |
| Works with AI agents through a local connection | Only clone voices you have permission to use |
GitHub - debpalash/VoiceStudio: VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages.
VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages. - debpalash/Voic…
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +946 · 📦 Total: 29,076
📜 License: Elastic License 2.0 · 👤 By: individual developer
🎯 Time to value: 5 minutes
📜 License: Elastic License 2.0 · 👤 By: individual developer
🎯 Time to value: 5 minutes
What it is: An add-on that keeps bulky tool output out of a coding agent's limited memory and saves session notes that survive when the conversation is trimmed. There was no new release today, just steady interest. Why you'd want it: Longer, cheaper coding-agent sessions before the agent forgets.
| ✓ Pros | ✗ Cons |
|---|---|
| Large claimed memory savings | License limits offering it as a hosted service |
| Session notes survive trimming | Savings figures are the author's own |
| Works across 17 agent tools | No release since June |
GitHub - mksglu/context-mode: Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.
Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks. - mksglu/context-mode
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +146 · 📦 Total: 49,292
📜 License: MIT · 👤 By: organization (K-Dense)
🎯 Time to value: 5 minutes
📜 License: MIT · 👤 By: organization (K-Dense)
🎯 Time to value: 5 minutes
What it is: A library of 177 "skills" (instruction packs) that teach AI coding agents how to use scientific software and databases in biology, chemistry, medicine and more. It is riding this week's wave of interest in agent skills. Why you'd want it: Give your agent real know-how for science tools instead of letting it guess.
| ✓ Pros | ✗ Cons |
|---|---|
| Free and permissively licensed | Large libraries can confuse agents (see today's arXiv paper) |
| Very broad science coverage | Medical outputs are research aids, not decisions |
| Works with many agent tools | Usage claims are self-reported |
GitHub - K-Dense-AI/scientific-agent-skills: Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 250,000+ scientists worldwide. 177 ready-to-use validated skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.
Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 250,000+ scientists worldwide. 177 ready-to-use validated skills plus 100+ scientific databases covering bio…
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +94 · 📦 Total: 52,455
📜 License: Apache-2.0 · 👤 By: university lab (University of Hong Kong)
🎯 Time to value: 10 minutes
📜 License: Apache-2.0 · 👤 By: university lab (University of Hong Kong)
🎯 Time to value: 10 minutes
What it is: A framework and community catalog that wraps desktop apps, such as LibreOffice and Obsidian, in text commands so AI agents can operate them. The project has been quiet for three weeks. Why you'd want it: Let an agent drive the apps you already use.
| ✓ Pros | ✗ Cons |
|---|---|
| Permissive license | Quality varies by community wrapper |
| Large catalog of supported apps | No updates for three weeks |
| Easy skill installs | Some wrappers edit app data, so back up first |
GitHub - HKUDS/CLI-Anything: “CLI-Anything: Making ALL Software Agent-Native” -- CLI-Hub: https://clianything.cc/
“CLI-Anything: Making ALL Software Agent-Native” -- CLI-Hub: https://clianything.cc/ - HKUDS/CLI-Anything
GitHub
Rank yesterday: not listed - New entry 🆕
⭐ Stars today: +2,143 · 📦 Total: 27,324
📜 License: Apache-2.0 · 👤 By: organization
🎯 Time to value: 10 minutes
📜 License: Apache-2.0 · 👤 By: organization
🎯 Time to value: 10 minutes
What it is: A free tool that audits whether an AI agent follows business rules, such as approvals, spending limits and authority, and gives it a graded scorecard. Today it added offline checks of an agent's past actions and a lab that finds allowed steps that combine into a forbidden result. Why you'd want it: A quick, repeatable check before an agent touches real workflows.
| ✓ Pros | ✗ Cons |
|---|---|
| Grades come from a different company's model, avoiding self-grading | Full test runs cost about $10-18 in AI fees |
| New offline audit needs no AI calls | A paid "Pro" tier is advertised |
| Permissive license | Scores depend on the tests you write |
GitHub - ifixai-ai/iFixAi: Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.
Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have…
GitHub
HuggingFace Trending
Top Models Today
Google's small multimedia search model held the top spot for a sixth day as downloads rose 8%.
📥 Downloads (30d): 135,175 · 📜 License: Apache-2.0
👤 By: Google · 🎯 Task: Feature extraction (embeddings)
📐 Size: 0.74B
👤 By: Google · 🎯 Task: Feature extraction (embeddings)
📐 Size: 0.74B
What it is: A small model that turns text, code, images, video and audio into number lists (embeddings) that can be searched together. It works in 100+ languages. Why you'd want it: One search index for documents, screenshots, video and audio, small enough for a laptop.
| ✓ Pros | ✗ Cons |
|---|---|
| Permissive license | Text gains over version 1 are small outside code |
| One index for every media type | Google's own benchmark numbers |
| Small enough for on-device search | Tool support still thin |
google/embeddinggemma-2 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Alibaba's Qwen image generator and editor, sped up to 8 steps, with downloads up 31% in a day.
📥 Downloads (30d): 12,704 · 📜 License: Qwen research license (non-commercial)
👤 By: Qwen (Alibaba) · 🎯 Task: Text-to-image
📐 Size: 7.1B
👤 By: Qwen (Alibaba) · 🎯 Task: Text-to-image
📐 Size: 7.1B
What it is: An official image model that both creates and edits pictures from text. This "Turbo" version needs only 8 steps per image. Why you'd want it: Fast local image generation and editing in one model.
| ✓ Pros | ✗ Cons |
|---|---|
| Official release from a major lab | Non-commercial license |
| Generation and editing together | Needs very new Diffusers software |
| Fast 8-step output | Unofficial uncensored copies are spreading |
Qwen/Qwen-Image-2.1-Turbo · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
OpenBMB's first mixture-of-experts vision model jumped from 630 to 4,157 downloads in a day.
📥 Downloads (30d): 4,157 · 📜 License: Apache-2.0
👤 By: OpenBMB · 🎯 Task: Image-text-to-text
📐 Size: 35B (about 3B active)
👤 By: OpenBMB · 🎯 Task: Image-text-to-text
📐 Size: 35B (about 3B active)
What it is: A model that reads images and answers questions about them, built from many specialist parts that switch on only as needed. The team says it runs on a phone at 13+ word pieces per second. Why you'd want it: Capable image understanding that can run on small devices.
| ✓ Pros | ✗ Cons |
|---|---|
| Permissive license | Phone speed relies on the team's own software fork |
| Built for phone-class devices | About 70 GB at full precision |
| Wide hardware support | Benchmarks are the team's own |
openbmb/MiniCPM-V-4.7-35B-A3B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
An open "decision model" whose downloads rose 61% as its makers pitched it for robots.
📥 Downloads (30d): 27,970 · 📜 License: Apache-2.0
👤 By: AutoTrust AI Lab · 🎯 Task: Text classification (decisions)
📐 Size: 36B (about 3B active)
👤 By: AutoTrust AI Lab · 🎯 Task: Text classification (decisions)
📐 Size: 36B (about 3B active)
What it is: A model that answers multiple-choice-style questions with calibrated probabilities across up to 256 options. Its makers now say it scores 51.3% on a robot-scene reasoning test with no robot training. Why you'd want it: Reliable, structured choices for software that needs a decision, not an essay.
| ✓ Pros | ✗ Cons |
|---|---|
| Permissive license | Benchmarks are self-scored |
| Up to 256 options per question | Small company |
| A compressed version fits one large chip | Compressed version needs the newest Nvidia chips |
autotrust/JEV-35B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
The go-to open video model slipped a few places but still leads on downloads.
📥 Downloads (30d): 1,823,507 · 📜 License: LTX community license
👤 By: Lightricks · 🎯 Task: Image-to-video
📐 Size: not listed
👤 By: Lightricks · 🎯 Task: Image-to-video
📐 Size: not listed
What it is: An open model that turns still images into video clips. It has a large community of add-ons for local video workflows. Why you'd want it: Make video on your own computer without a subscription.
| ✓ Pros | ✗ Cons |
|---|---|
| Runs locally | License has revenue limits |
| Large add-on ecosystem | Needs a lot of graphics memory |
| Proven, widely used | Size not published on the model page |
Lightricks/LTX-2.5 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A laptop-sized decision model that answers typed questions in milliseconds.
📥 Downloads (30d): 14,854 · 📜 License: LFM 1.0
👤 By: Liquid AI · 🎯 Task: Image-text-to-text (decisions)
📐 Size: 3.1B
👤 By: Liquid AI · 🎯 Task: Image-text-to-text (decisions)
📐 Size: 3.1B
What it is: A small model built to make quick structured decisions, about 8 milliseconds each on a high-end gaming graphics card, per its makers. It now faces a hosted rival, Bespoke Labs' Nimble. Why you'd want it: Fast decisions on your own hardware.
| ✓ Pros | ✗ Cons |
|---|---|
| Small enough for edge devices | Custom license |
| Very low latency | Requires running the makers' own code |
| Handles images too | Speed figures are the makers' own |
LiquidAI/d1-3B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Fish Audio's new open voice model for multi-character scenes and voice cloning entered the trending list.
📥 Downloads (30d): 839 · 📜 License: Fish Audio research/community license
👤 By: Fish Audio · 🎯 Task: Text-to-speech
📐 Size: 36B (about 3B active)
👤 By: Fish Audio · 🎯 Task: Text-to-speech
📐 Size: 36B (about 3B active)
What it is: A text-to-speech model that can voice up to 16 characters in one script, clone a voice from a short clip and re-record a single word in context. Its makers report first audio in about 89 milliseconds on one data-center graphics chip. Why you'd want it: Audio drama, dubbing or narration with several voices from one open model.
| ✓ Pros | ✗ Cons |
|---|---|
| Multiple speakers and cloning in one model | Commercial use only under $500,000 yearly revenue |
| Very fast first audio | Needs a data-center-class graphics chip |
| Ready-made serving support | Clone only voices you have permission to use |
fishaudio/drama-3 · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Liquid AI's largest small-footprint model, built for fast private agents on your own device.
📥 Downloads (30d): 4,067 · 📜 License: LFM 1.0
👤 By: Liquid AI · 🎯 Task: Text generation (reasoning)
📐 Size: 24B (about 2.4B active)
👤 By: Liquid AI · 🎯 Task: Text generation (reasoning)
📐 Size: 24B (about 2.4B active)
What it is: A reasoning model that uses only about a tenth of its parts for each word, so it runs quickly on laptops. Its makers report 184 word-pieces per second on an Apple M5 Max. Why you'd want it: A capable agent model that keeps your data on your machine.
| ✓ Pros | ✗ Cons |
|---|---|
| Laptop-class speed | Custom license, so check commercial terms |
| Many ready formats for local apps | Weak on facts without a search tool |
| Long 128K-token memory | Comparisons are the makers' own |
LiquidAI/LFM2.5-24B-A2B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Product Hunt
AI Launches Today
The Vercel for GTM
🔥 Upvotes: 487 · 👤 By: Tristan Comte and team
💰 Pricing: paid from $99/month, 7-day trial credits · 🏷 Category: Sales and marketing
💰 Pricing: paid from $99/month, 7-day trial credits · 🏷 Category: Sales and marketing
Pancake gives an AI agent such as Claude or Codex sales and marketing building blocks through one connection. It learns your ideal customer from your website, pulls leads from 30+ data providers, watches for signals like funding rounds and sends outreach from your account after you approve each lead. It led Wednesday's board at time of writing. Verdict: Removes a lot of glue work and keeps a human approving every lead, but it is still automated cold outreach, and the trial needs a card.
Pancake: The Vercel for GTM | Product Hunt
Pancake is the Vercel for GTM. It gives you the building blocks to deploy any go-to-market idea from your favorite AI agent, such as Claude or Codex: a GTM Brain, sending infrastructure, and 40+ data providers and enrichment, all accessible through one MCP connection.
Product Hunt
Free AI browser agent: find leads, reach out, apply to jobs
🔥 Upvotes: 200 · 👤 By: rtrvr.ai
💰 Pricing: free with ads, paid from $9.99/month · 🏷 Category: Browser automation
💰 Pricing: free with ads, paid from $9.99/month · 🏷 Category: Browser automation
A Chrome extension and cloud browser agent that finds leads, sends outreach, fills job applications, scrapes sites into spreadsheets and monitors pages. The free mode shows sponsored cards inside your agent runs. Verdict: A genuinely free way to try a browser agent, but "free" means ads, and mass outreach or applications can break site rules.
Retriever AI: Free AI browser agent: find leads, reach out, apply to jobs | Product Hunt
Ask Retriever to find leads and send outreach, shortlist TikTok and Instagram creators, apply to jobs or even help with homework. Use it free (inference included) in Chrome or the cloud, entirely ads supported, no API key or subscription needed!
Product Hunt
Intent verification for coding agents
🔥 Upvotes: 153 · 👤 By: the team behind Qase
💰 Pricing: 14-day trial, paid from $49/month · 🏷 Category: Developer tools
💰 Pricing: 14-day trial, paid from $49/month · 🏷 Category: Developer tools
Tiden checks that code written by Claude Code, Cursor, Codex or Copilot does what you actually asked. It keeps written "promises" about your product beside the code, flags ones no test proves and gives one pass or fail verdict per release. Verdict: Targets the real gap where an agent's own tests just agree with its own code, but per-change pricing adds up fast for busy projects.
Tiden: Intent verification for coding agents | Product Hunt
Tiden verifies your coding agents built what you actually asked for. Most checks run inside the session that wrote the code, so the tests agree with it by construction. Tiden keeps your intent as requirements that branch and merge like code, and checks every change against that record. The verdict comes from tests run in your environment; no model grades the diff. You decide what merges, and production errors trace back to the release. Works beside Claude Code, Cursor, Codex and Copilot.
Product Hunt
A state-of-the-art coding agent for cost efficiency
🔥 Upvotes: 102 · 👤 By: Reason Machines
💰 Pricing: free to start, paid pricing not listed · 🏷 Category: AI coding
💰 Pricing: free to start, paid pricing not listed · 🏷 Category: AI coding
A coding agent that takes a task, writes and tests code and opens a pull request, from a Mac app, terminal, web or Slack. You choose the AI models, and it claims to be 22% cheaper than rival agent setups. Verdict: Cost per task is the right thing to compete on, but the benchmark and savings claims are the company's own.
Reason: A state-of-the-art coding agent for cost efficiency | Product Hunt
Reason is a state-of-the-art coding for cost efficiency. We scored higher than harnesses like Codex & Pi on benchmarks like Terminal Bench 4.0 and DeepSWE while being 22% cheaper. Reason can work in the cloud or locally. Give it a task and it writes code, runs tests and opens a pull request. Use Reason from the Mac app, terminal, web or Slack, with your choice of models and connected subscriptions. Start free on your own computer or cloud!
Product Hunt
SOTA Decision Model
🔥 Upvotes: 80 · 👤 By: Bespoke Labs
💰 Pricing: free to try, paid pricing not listed · 🏷 Category: AI models
💰 Pricing: free to try, paid pricing not listed · 🏷 Category: AI models
Hosted "decision models" that take typed questions and return calibrated choices. Bespoke Labs claims 43% fewer mistakes than rival model Jev in its internal tests. Verdict: A credible lab joining a hot category, but every number is self-reported, so test it against open rivals on your own questions.
Nimble: SOTA Decision Model | Product Hunt
Today, we are announcing Nimble-v4 and Nimble-v4-max which are pushing the frontier of decision models, outperforming Jev and other variants. On Decision Index public scores, our nimble-v4-max model and nimble-v4 models score +10.5 and +5.74 against Jev 1.13, making nimble-v4-max a top performing model. Beyond benchmarks, we have done a lot of internal evals, and see big improvements: 43% fewer mistakes than Jev, +50pp on model routing decisions, and so on. Try for free: console.bespokelabs.ai
Product Hunt
API Pricing
Snapshot
| Provider | Model | Input $/1M | Output $/1M | Context |
|---|---|---|---|---|
| Anthropic | Claude Fable 5.1 | $10.00 | $50.00 | 1M tokens |
| Anthropic | Claude Opus 5.5 | $4.00 | $20.00 | 1M tokens |
| Anthropic | Claude Sonnet 5.5 | $2.00 | $10.00 | 1M tokens |
| Anthropic | Claude Haiku 5.5 | $0.10 (up to 100K-token prompts; $0.50 above) | $0.50 ($2.50 above 100K) | 1M tokens |
| OpenAI | GPT-6 Astra | $10.00 (up to 272K-token prompts; $20.00 above) | $50.00 ($75.00 above 272K) | 1.05M tokens |
| OpenAI | GPT-6.1 Sol | $2.00 (up to 272K; $4.00 above) | $10.00 ($15.00 above 272K) | 1.05M tokens |
| OpenAI | GPT-6 Luna | $0.10 (up to 272K; $0.20 above) | $0.50 ($0.75 above 272K) | 1.05M tokens |
| Gemini 4 Argon | $2.00 to Nov 30; $4.00 from Dec 1 | $10.00 to Nov 30; $20.00 from Dec 1 | 1M tokens | |
| Gemini 3.8 Flash | $0.75 (to Dec 31; $1.50 from Jan 1) | $3.75 (to Dec 31; $7.50 from Jan 1) | not listed | |
| Groq | GPT-OSS 120B | $0.15 | $0.60 | 131K tokens |
| Groq | Qwen3.8-27B | $0.80 | $4.00 | 131K tokens |
No list-price changes vs. October 13 - the seventh straight day of stable prices. Google's pricing page now also shows an invite-only "Contributor" tier at half the standard price, though it is unclear when it appeared.
What this means: Gemini 4 Argon's introductory price has 47 days left. Until November 30 it costs the same as GPT-6.1 Sol and Claude Sonnet 5.5; from December 1 it matches Claude Opus 5.5.
What this means: Gemini 4 Argon's introductory price has 47 days left. Until November 30 it costs the same as GPT-6.1 Sol and Claude Sonnet 5.5; from December 1 it matches Claude Opus 5.5.
arXiv Paper of the Day
Lost in Implicit Routing: How LLM Agents Fail to Load Relevant Skills at Scale
Jinlin Liu, Wei Chen, Xiaojin Zhang · arXiv:2610.18522
What it claims: AI agents load add-on "skills" (instruction packs) by reading their descriptions, and this stops working well as the library grows. Picking the right skills in a separate step before the agent starts largely fixes the problem.
Key finding: With 1,000 irrelevant skills installed, the share of relevant skills actually loaded fell from 73.6% to 27.4%, while choosing skills up front kept it at 73.9%.
Why practitioners should care: If you install dozens or hundreds of skills into Claude Code, Codex or Cursor, you may be getting less from them without noticing, because tasks often still pass. Keep libraries small, preselect skills for large ones and log which skills actually load. Caveats: one benchmark, mostly open-weight models.
Key finding: With 1,000 irrelevant skills installed, the share of relevant skills actually loaded fell from 73.6% to 27.4%, while choosing skills up front kept it at 73.9%.
Why practitioners should care: If you install dozens or hundreds of skills into Claude Code, Codex or Cursor, you may be getting less from them without noticing, because tasks often still pass. Keep libraries small, preselect skills for large ones and log which skills actually load. Caveats: one benchmark, mostly open-weight models.
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