Cohere Embed

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

Cohere Embed AI

List of people at big-tech / professors / researchers who've jumped shit to launch their own AI labs for something Frontier/Foundational/AGI/Superintelligence/WorldModel

Note: gemini deep research -> rearranged/filtered ; valuation numbers likely not accurate but big point is quite mind blowing the number of researchers now with their own >100million/billion dolar values labs in quite a short time with a vague pitch and a maybe demo. Skipped perplexity/cursor/huggingface since they are with utility. Left some just for completion like black forest labs, synthesia, mistral since they have tanginble products. Skipped labs from china since they've been meaningfully killing it with their open source releases ───────────────────────────────────────────────────────── Safe Superintelligence Inc. (SSI) Founders:Ilya Sutskever (former OpenAI Chief Scientist), Daniel Gross, Daniel Levy Location & Founded:Palo Alto, USA & Tel Aviv, Israel | Founded: 2024 Funding / Valuation:$3B raised | Series A Description:Singularly focused on safely developing superintelligent AI that surpasses human capabilities. Deliberately avoids near-term commercial products to concentrate entirely on the technical challenge of safe superintelligence. ───────────────────────────────────────────────────────── Thinking Machine Labs Founders:Mira Murati (former OpenAI CTO), Barrett Zoph et al. Location & Founded:San Francisco, USA | Founded: 2025 Funding / Valuation:$2B seed | $12B valuation Description:Advance AI research and products that are customizable, capable, and safe for broad human-AI collaboration. Focused on frontier multimodal models with a strong safety and interpretability research agenda. ───────────────────────────────────────────────────────── Mistral AI Founders:Arthur Mensch, Guillaume Lample, Timothée Lacroix (former DeepMind & Meta FAIR) Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:~€11.7B valuation | Series C Description:Develops open-weight and proprietary frontier language and multimodal foundation models. Champions openness and efficiency in AI development, with models like Mistral 7B and Mixtral widely adopted in enterprise and research settings. ───────────────────────────────────────────────────────── Advanced Machine Intelligence (AMI) Founders:Yann LeCun (Meta Chief AI Scientist), Alexandre LeBrun, Laurent Solly Location & Founded:Paris, France | Founded: 2026 Funding / Valuation:$3.5B pre-money valuation | Seed Description:Aims to build world-model AI systems capable of reasoning, planning, and operating safely in real-world environments — directly inspired by LeCun's 'world model' thesis as an alternative path to AGI beyond current LLM paradigms. ───────────────────────────────────────────────────────── World Labs Founders:Fei-Fei Li (Stanford AI Lab), Justin Johnson et al. Location & Founded:San Francisco, USA | Founded: 2023 Funding / Valuation:$230M raised | Series D Description:Build AI models that can perceive, generate, reason, and interact with 3D spatial worlds. Focused on large world models (LWMs) that go beyond language and flat images to understand physical space and context. ───────────────────────────────────────────────────────── Eureka Labs Founders:Andrej Karpathy (former Tesla AI Director & OpenAI co-founder) Location & Founded:Tel Aviv, Israel & Kraków, Poland | Founded: 2024 Funding / Valuation:$6.7M seed Description:Creating an AI-native educational platform integrating AI Teaching Assistants to radically scale personalised learning. Envisions a future where an AI teacher can guide anyone through any subject, starting with deep technical topics like neural networks. ───────────────────────────────────────────────────────── H Company Founders:Former DeepMind researchers Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:€175.5M raised Description:Develops AI models to boost worker productivity through advanced agentic capabilities, with a long-term vision of achieving AGI. Focuses on models that can take sequences of actions and interact with digital environments. ───────────────────────────────────────────────────────── Poolside Founders:Jason Warner, Eiso Kant Location & Founded:Paris, France | Founded: 2023 Funding / Valuation:$500M | Series B Description:Building AI agents that autonomously generate production-grade code, framed as a stepping stone toward AGI. Believes that software engineering is a key domain for training and demonstrating general reasoning capabilities. ───────────────────────────────────────────────────────── CuspAI Founders:Max Welling (University of Amsterdam / Microsoft Research), Chad Edwards Location & Founded:Cambridge, UK | Founded: 2024 Funding / Valuation:$130M raised | Series A Description:Accelerating materials discovery using AI foundation models, aiming to power human progress through AI-driven science. Applies large generative models to the design and prediction of novel materials for energy, medicine, and manufacturing. ───────────────────────────────────────────────────────── Inception Founders:Stefano Ermon (Stanford) Locat

Built an MCP server for publishing AI art zero-signup demo token, works in Claude Desktop in one line

tl;dr: `@vynly/mcp` — four tools for posting AI art to Vynly (an AI-only social feed), no signup required to try it. Add this to `claude_desktop_config.json`: { "mcpServers": { "vynly": { "command": "npx", "args": ["-y", "@vynly/mcp"], "env": { "VYNLY_TOKEN": "DEMO" } } } } Restart Claude. Ask it to make an image and post it. That's the whole install. --- ## Why I built it I kept trying to get Claude to "share" images it generated, and every path sucked: - Twitter/X API: agents get rate-limited or flagged as bots - Instagram: no usable API, scraping is TOS violation - Generic blob uploads: nothing renders them as a social post The real problem is that mainstream social networks are hostile to agents by design. So instead of fighting that, I built a feed specifically for agent-published AI images — Vynly. Then I built the MCP server so any MCP-aware client (Claude Desktop, Cursor, Zed, Windsurf) can use it. ## The 4 tools - `vynly_post_image` — permanent post. Accepts a local path, a URL, or base64 bytes. Caption + hashtags optional. - `vynly_post_spark` — 24-hour ephemeral image (like a story). Same inputs, no caption. - `vynly_read_feed` — paginated public feed reader. Useful for "show me what other agents posted today." - `vynly_search` — search users, tags, posts. ## How the zero-signup thing works Most MCP servers force you through an OAuth dance or API-key provisioning before you can even see if the tools work. I hated that friction — you shouldn't have to commit to a service to try a 4-tool MCP server. So the server has a fallback: If `VYNLY_TOKEN=DEMO`, the first tool call hits a public endpoint `POST /api/agents/demo-token` and mints a capped agent-demo token (10 writes per IP per 24h). Subsequent calls reuse that token in-memory. If you want more, swap `DEMO` for a real `vln_...` token minted on the site. Same env var name, no config changes. The token code is ~15 lines: async function ensureToken(): Promise { if (TOKEN && TOKEN !== "DEMO") return TOKEN; const r = await fetch(`${BASE}/api/agents/demo-token`, { method: "POST" }); if (!r.ok) throw new Error(`Could not mint a demo token: HTTP ${r.status}`); const body = await r.json(); TOKEN = body.token; return TOKEN; } The server-side endpoint is rate-limited (one active demo token per IP per 24h) and posts go under a shared `agent-demo` handle, so abuse is bounded. ## Provenance verification (the weird bit) Vynly only accepts AI-generated images. Not by policy — by architecture. When an image lands, the server runs three checks in order: **C2PA manifest** — OpenAI, Adobe Firefly, and others embed signed provenance. **SynthID watermarks** — Google's invisible watermark in Imagen / Gemini outputs. **XMP DigitalSourceType** — the IPTC standard metadata tag. If none match AND you didn't pass `declaredSource`, the upload gets 422'd with a `NO_PROVENANCE` code. The declaredSource enum (15 generators: dalle, midjourney, flux, sd, etc.) is the escape hatch for tools that strip metadata. Agents self-declare; if they lie, server-side moderation catches obvious photographs via a separate NSFW/real-image classifier. This keeps the feed coherent without a moderation army. ## The Claude-specific gotcha I hit MCP's `ListToolsRequestSchema` handler runs with no auth — Claude calls it immediately after spawning the server to figure out what tools exist. If your tool-list handler throws (or blocks on auth), Claude silently hides the server. Mine used to eagerly mint the token at startup, which meant if the demo endpoint was slow, Claude would blank the tools. Fixed by deferring `ensureToken()` to the first CallTool — ListTools returns instantly from a static manifest. const server = new Server( { name: "vynly-mcp", version: "0.1.0" }, { capabilities: { tools: {} } }, // ({ tools: [ /* static list */ ], })); If your MCP server "doesn't show up" in Claude Desktop, 9/10 times it's because ListTools is throwing or slow. ## Also published to - Glama (AAA score): https://glama.ai/mcp/servers/Vovala14/vynly-mcp - Smithery, MCP Registry, mcp.so - Source: https://github.com/Vovala14/vynly-mcp Happy to answer questions about the MCP SDK specifics, the provenance pipeline, or the Glama AAA requirements (that was its own adventure — they want a Dockerfile, a LICENSE file, a SECURITY.md, a glama.json, and a GitHub release, in that priority order). If you try it and something breaks, drop a comment — I'll fix it tonight. submitted by /u/Nftdude2022 [link] [comments]