Hasitha Chandrasekara @Hasitha_Ch

Outlook where frontier AI is headed next 18 months: The AI reasoning training + harness loop works if you can produce enough data and reasoning traces (via verifiers). Proven with code and math results. Frontier labs desire to scale this horizontally to many more domains as increasing generality isn't emerging from the NN substrate through data/scale. But it's very expensive and slow to do this training loop manually. Enter "RSI" discourse. Labs want to automate this training loop they now know works. How? By leveraging coding agents to build world models aka symbolic verifiers. The bet is automated horizontal domain scaling through automatic symbolic world modeling which offers the critical feedback into post-training. This is important because many domains are intolerant of learning "online". Symbolic world models offer a path to learning/training "offline". It's safe for an AI system to test hypotheses against a git repo with tests with no consequences. It's not safe for AI to test against online systems eg SaaS databases, tax filings, manufacturing spin up, etc. A couple other trends to overlay. We're seeing incredible capabilities emerge from better symbolic harnesses around frontier reasoning models. As time goes forward these harnesses produce the necessary training traces required to teach the models to emulate the harness, obviating the need for the fat harness. The other related push is towards multi-agent scaling. Many problems are search constrained (we see this in math right now) where a single linear CoT is not the optimal way to find a solution when you're optimizing for time.

CODEX SKILL THAT FINDS YOUR STARTUP’S FIRST CUSTOMERS! I made a Codex skill that analyzes your startup and finds potential customers from real public signals. Paste your startup URL while Codex defines your ideal customer, searches public discussions, qualifies each prospect, and generates a polished report with personalized outreach openers. -> ideal customer profile analysis -> public pain + buying signal research -> evidence-backed prospect shortlist -> fit, timing + reachability scores -> original source links for every prospect -> personalized outreach openers -> polished HTML report -> one-command install Install: npx --yes codex-first-customer-finder-skill 100% open source. Repo in Bio.

Après deux heures à regarder le lac, j'ai réalisé que c'était la clôture du voisin

Today, we’re excited to introduce Miso One, the most emotive voice model in the world. Miso One is an 8-billion-parameter text-to-speech model for highly expressive speech generation. It emotes like a human and responds faster than a human, with just 110 milliseconds of latency. We’ve open-sourced the model weights, with API access coming soon. Hear how Miso One sounds in the thread below.

Meet "Tawan" (ตะวัน means “The sun” 🌞) 20-min Demo AI Animated Film experiment (full feature is 90 mins) With a $500 budget and 1.5 months of work, this story is based on my original idea from 2010... and today, the technology is finally ready to bring it to life. AI showed me that solo creators can now manage an entire animation workflow. No need to pitch to big studios—you can fund yourself and bring your own stories to life. Without AI, this would still be stuck in my head. (Of course, the quality is still far from high-budget films from big studios that have 300-600 people behind them, but I think the gap will close step by step in the future.) This animated created by Seedance 2.0 on @dreamina_ai and @kinovi_ai and opening scene by @midjourney - thank you for watching.

A 6-person team is building task-specific AI models that are 4-8x faster than anything from OpenAI or Anthropic. 500K downloads on HuggingFace. No hype. Just better engineering winning on the merits. This is what "make something people want" looks like in the model layer. zeroentropy.dev

INCREDIBLE The MOST COMPLETE GUIDE for understanding LLMs from first principles is now available online to read for free Covers the model mechanics - Tokens / tokenizers - Transformers - Attention - KV cache - Prefill vs decode - Decoding controls - Model packages - Chat templates - Long context - RAG - Agents / tools - Fine-tuning - Multimodal models Then connects that to running models locally - What "local" really means - Open-weight vs opensource - Quantization - VRAM math - Hardware tiers - File formats / load safety - Runtimes / serving modes - Model selection - Privacy - Failure modes - Benchmarks - Practical setup paths You should read this, and if you cannot now then you most definitely wanna bookmark it for later Opensource AI FTW

Ahmad @TheAhmadOsman

3 months ago

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New work with @AlecRad and @DavidDuvenaud: Have you ever dreamed of talking to someone from the past? Introducing talkie, a 13B model trained only on pre-1931 text. Vintage models should help us to understand how LMs generalize (e.g., can we teach talkie to code?). Thread:

What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS

@bryan_johnson Quick 1 prompt infograph!

This works really well btw, at the end of your query ask your LLM to "structure your response as HTML", then view the generated file in your browser. I've also had some success asking the LLM to present its output as slideshows, etc. More generally, imo audio is the human-preferred input to AIs but vision (images/animations/video) is the preferred output from them. Around a ~third of our brains are a massively parallel processor dedicated to vision, it is the 10-lane superhighway of information into brain. As AI improves, I think we'll see a progression that takes advantage: 1) raw text (hard/effortful to read) 2) markdown (bold, italic, headings, tables, a bit easier on the eyes) <-- current default 3) HTML (still procedural with underlying code, but a lot more flexibility on the graphics, layout, even interactivity) <-- early but forming new good default ...4,5,6,... n) interactive neural videos/simulations Imo the extrapolation (though the technology doesn't exist just yet) ends in some kind of interactive videos generated directly by a diffusion neural net. Many open questions as to how exact/procedural "Software 1.0" artifacts (e.g. interactive simulations) may be woven together with neural artifacts (diffusion grids), but generally something in the direction of the recently viral x.com/zan2434/status… There are also improvements necessary and pending at the input. Audio nor text nor video alone are not enough, e.g. I feel a need to point/gesture to things on the screen, similar to all the things you would do with a person physically next to you and your computer screen. TLDR The input/output mind meld between humans and AIs is ongoing and there is a lot of work to do and significant progress to be made, way before jumping all the way into neuralink-esque BCIs and all that. For what's worth exploring at the current stage, hot tip try ask for HTML.

Thariq @trq212

3 months ago

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@umar_mashoor @Dailymirror_SL Na, just geopolitics and we never had it in the first place.

The countries that developed in the post-WWII period share one variable more consistently than any cultural or ethnic characteristic: Strategic value to the United States during the Cold War. South Korea: essential. Fully developed. Taiwan: essential. Fully developed. Singapore: strategically useful. Developed. Israel: essential. Massively subsidized, still today. Western Europe: essential. Marshall Plan. Japan: essential. Rebuilt from occupation. Countries with limited Cold War strategic value, or whose development was contrary to Western corporate interests: Ghana: destabilized. Congo: leader assassinated, replaced with Mobutu, looted for thirty-two years. Chile: democratic socialist government removed by coup, replaced with Pinochet, opened to Chicago School experiment. Iran: democratic government removed in 1953, replaced with Shah, resources extracted until 1979. Vietnam: destroyed. Nicaragua: destabilized. Bolivia: multiple coups. The pattern is not cultural. The pattern is strategic. Develop what serves American power. Destabilize what threatens it. Present both outcomes as the natural result of the affected populations' own characteristics.

🚀 DeepSeek-V4 Preview is officially live & open-sourced! Welcome to the era of cost-effective 1M context length. 🔹 DeepSeek-V4-Pro: 1.6T total / 49B active params. Performance rivaling the world's top closed-source models. 🔹 DeepSeek-V4-Flash: 284B total / 13B active params. Your fast, efficient, and economical choice. Try it now at chat.deepseek.com via Expert Mode / Instant Mode. API is updated & available today! 📄 Tech Report: huggingface.co/deepseek-ai/De… 🤗 Open Weights: huggingface.co/collections/de… 1/n

Sri Lanka is testing the Metro Bus Digital Platform (MBDP) by Lanka Metro Transit pilot launching this April on Makubura–Pettah & Kadawatha routes. • Real-time bus tracking • Tap-in/Tap-out mobile payments • Centralized smart transport system #DigitalSriLanka #SriLanka #LKA

Midjourney -> Seedance 2.0: Continuous shot Prompt below:

This tool can download literally anything from link 🤯 100% free. open source. no ads.

There is a special heaven for people who upload pictures of restaurant menus to Google Maps.

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Chris Manning says Yann LeCun sees language as a low bandwidth communication channel compared to vision. But the gap between a chimp and a human wasn’t produced by superior eyes. What took off for humans was language. Not just for communication, but as a cognitive tool.

@sundarpichai 4 mins till April fools here.