Al Enthusiast | Ghostwriter | Empowering buisness models & personal brands to grow with latest tech trends. DM for collab ✉️
Florida, USA
Joined April 2022
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GPT-style chat is cool.
But agentic execution is the real battleground now.
Ring-2.6-1T looks engineered for exactly that:
orchestration, routing, coding, planning, and reliable long workflows ⚡
We are launching Ring-2.6-1T, a trillion-parameter flagship thinking model engineered for real-world complex tasks and production env: 🚀
- Adjustable Thinking Effort: dynamic compute mechanism to flexibly balance cognitive depth, token cost, and execution speed;
- Agent-Optimized: Built for high-frequency workflows, delivering rapid multi-step execution and tool orchestration with SOTA stability;
- Deep Thinking: Unlocks the model's maximum capability ceiling for rigorous mathematical logic and scientific research;
AI winners won’t just build better models—they’ll build better infrastructure.
One interface for image, video, 3D, and audio lets teams test and ship faster, without constantly rewriting integrations.
That edge is bigger than it looks.
🤝 Paid partnership
Comfy Router is live
One API for frontier image, video, 3D, and audio models.
Same model string. Same arguments. No new SDK, no new key, no redeploy.
What Comfy Router gives you:
→ Explicit routing. You name the provider, we call that provider. It's down? The request fails there. No silent fallback.
→ Every job returns the provider that ran it. Log it, bill it, debug it.
→ Async. submit() returns a request ID immediately. The queue retries 429s and transient errors until a slot opens. subscribe() submits and polls to completion.
→ Batch-friendly. Queue a few hundred jobs, hold the IDs, pull results as they land. Nothing blocking on a 5-min video render.
→ 24h retention on inputs and outputs, then deleted.
→ Comfy credits. No sub, no Router fee.
Providers at launch: Comfy. Runware, Wavespeed, Fal, Higgsfield. Multi-provider where the model supports it.
Get Your API Key with the link below. ⬇️
The companies that win the next decade won't just automate tasks.
They'll automate momentum.
We raised $21M to help small businesses beat the giants
We're giving $1M of it back to you today
Today we're launching Runable Grow: world's first agent that runs your entire go-to-market. 24/7
The last few months have been unreal.
Millions of users came to @runable_hq and built their entire business on it, websites, databases, payments, analytics, pitch decks, product videos & scheduled work.
Every single one of them asked the same question:
"How do I grow it?"
So we built the answer.
Runable Grow handles GTM end-to-end:
→ Runs ads on Meta, Google, and ChatGPT without any account, fully managed by Runable
→ Cold calls + cold emails from a real phone number and your business inbox
→ Generates and qualifies leads
→ Social listening
→ SEO + AEO optimization
Not a dashboard. Not a "copilot."
An agent that does the work.
It's a world-class media buyer, SDR, SEO lead, brand analyst working for your business while you sleep.
Don't believe me? Prove me wrong.
Your first $100 on Grow is on us. Every paid user. No catch.
Go break it 👇 runable.com
Sales is quietly entering its AI-native era. 3x more meetings isn't a productivity hack. It's a different operating model.
Today, we're launching Monaco into General Availability.
We onboarded several hundred hypergrowth startups during our beta. The results are staggering:
The average customer added 16 percentage points to their month-over-month revenue growth rate.
The average customer tripled their monthly meeting volume.
With today's release, Monaco is now the most advanced AI sales platform in the world.
Monaco customers have an unfair competitive advantage.
We celebrate AI replacing meetings.
I'd rather see AI remove the bureaucracy that delays real patient care. This feels like a much bigger opportunity.
🤝 Paid partnership
We raised $22.5M to fix both halves of the custom medical device supply chain: the paperwork that blocks them and the manufacturing that slows them.
In America 🇺🇸, it's easier to prescribe a patient opioids than to get them custom insoles to prevent amputation. Three generations of my family watched that up close and couldn't fix it. Here's what we've built @HikeMedAI :
397B Isn't the Headline
397B parameters gets attention.
Self-improvement gets mine.
Ornith-1.5 can generate tasks, build scaffolds, create solution rollouts, and use them for reinforcement learning.
The future of scaling may be about more than parameters.
🤝 Paid partnership
Aloha! 🌺Introducing Ornith-1.5, a family of open-source LLMs spanning 9B Dense, 35B MoE, and 397B MoE, trained with self-improving strategies.
It achieves state-of-the-art performance among open-source models of comparable size and delivers performance comparable to Claude Opus 4.8 across reasoning, agentic, and coding tasks:
✅Terminal-Bench 2.1 (86.1)
✅SWE-Bench (86 on verified, 65.1 on pro, 79.6 on Multilingual)
✅DeepSWE (56)
✅HLE (44.6)
✅ClawEval (81.4)
✅Tool Decathlon (71.2)
Ornith-1.5 takes a major step toward training foundation models through end-to-end self-improvement, extending the self-scaffolding strategies introduced in Ornith-1.0 into a more complete self-improvement loop: the model proposes new tasks, generates task-specific scaffolds, and produces solution rollouts for reinforcement learning, continuously creating new learning experiences from which it can improve.
All models, along with their quantized versions (FP8, GGUF, MLX, and NVFP4), have been released under the MIT License, enabling unrestricted commercial and research use.
📘Tech Blog: ornith.ai/ornith_1_5.html
🤗Huggingface: huggingface.co/collections/o…
The wild part isn’t 28B.
It’s 28B + 10M context + strong agentic performance + single-GPU deployment.
That combination makes Pokee-Isaac 28B seriously hard to ignore.
🤝 Paid partnership
Meta just released Muse Glimmer 30B. So we put it side-by-side with Pokee-Isaac 28B, Qwen3.6 27B, and Gemma 4 31B.
Same ~30B weight class. Same evaluation environment.
Pokee-Isaac leads across every agentic benchmark we tested:
BFCL v4: 70.94
τ³-bench: 66.67
Terminal-Bench 2.1: 65.12
MCP-Atlas: 74.59%
And then there’s Pokee-Isaac's unique long-context capabilities:
93.3% RULER at 10M context
0.5 MRCR v2 at 1M token context
where all other models score 0!
All in a 28B model deployable on a single GPU.
The ~30B local frontier is getting very interesting.
Bigger isn't always better. Ling 3.0 Tiny proves you can get serious reasoning, local inference, and tool use from a model that activates just
1.3B parameters per token. Efficient AI is becoming the new competitive advantage.
Long-context AI only matters if it can actually reason across that context.
Leading benchmarks like BFCL v4 and τ³-bench, combined with a 93.3% RULER score at 10M tokens, suggest Pokee-Isaac 28B isn't just remembering more—it's using that information effectively.
🤝 Paid partnership
Releasing Pokee-Isaac 28B — the world’s first real 10M-token context frontier-class agentic model, deployable on a single GPU (starting from RTX 4090 or equivalent).
New proprietary non-decoder-only architecture:
• 93.3% RULER at 10M tokens
• Up to 137K tokens/s prefill on one B200 with 10M-token context
• Leads BFCL v4 and τ³-bench in our evaluation
• Lowest combined attack success rate among evaluated models on DTAP security red-teaming benchmark
Pricing and deployment:
💰 $0.15/M input · $1/M output
🔒 Deploy in your VPC, on-premises, or on-device, with Day-0 support for @vllm_project and @sgl_project
Technical blog: console.pokee.ai/model
Technical report: console.pokee.ai/pokee-isaac…
API: console.pokee.ai
Why create another podcast when AI can create an entire production? The bar for content just moved higher.
🤝 Paid partnership
Video Podcast is live.
Turn any doc, link, or idea into a two-host video show with studio scenes, multi-cam cuts, and B-roll. Ready in minutes.
Everyone else stops at audio. This is a show you can publish.
Try it: app.heygen.com/apps/video-po…
A model built for production scale agents and free to use until August 3.
That's the kind of launch more AI teams should be doing. Lower the barrier and let the community decide.
🤝 Paid partnership
The future of business is borderless.
Your financial platform should be too.
Flex Global is built for companies that think beyond one market and plan for worldwide growth.
🤝 Paid partnership
Alpha AI retweeted
🏆 $10,000+ in prizes
🔥 The hottest AI developer tools — all in one place.
🌟 100+ AI engineers from top AI Labs
🚀 The BIGGEST AI Hackathon of the Summer is here.
Alpha AI retweeted
Shanghai AI Lab just published a 58-page position paper trying to settle what "world model" actually means. Their definition quietly demotes Sora-style video generation from main event to side effect. Worth breaking down.
Alpha AI retweeted
Nobody tweets demos of policy evaluation, but this is the part of world models where the money is.
The real bottleneck in robotics right now: policies improve faster than anyone can physically test them. 324k simulated rollouts to grade policies attacks exactly that. The one number I'd want before trusting it, though, is the correlation between world-model score and real-world success rate. Policies exploit simulator errors. A great score inside the model can just mean the policy found the blind spots. The old model-based RL crowd had a name for this: hallucinating value.
Generation gets the demos. Evaluation gets the deployment.
Alpha AI retweeted
You can watch a million hours of people pouring coffee and still not know the wrist adjustment that keeps the cup from tipping.
That's the core problem this paper is attacking. Internet video teaches appearance; it doesn't teach action. Hence the number that matters here: 70,000 hours of embodied footage folded into web-scale pretraining. Huge by embodied standards, three orders of magnitude smaller than the web corpus it's mixed into. That gap (pyramid below) is the constraint the whole field is optimizing against — and the physics-consistency gains they report suggest the middle layer punches way above its weight per hour.
A video model that's built for robots!
As most video models learn appearance, this paper LingBot-Video tries to learn action, motion, and physical cause-and-effect.
It does this by scaling a sparse MoE video diffusion model, mixing internet video with 70k hours of robot, navigation, and egocentric footage, and training it with rewards for physical plausibility and task success.
So they basically turned a video model into a world model for embodied intelligence.
Alpha AI retweeted
Most AI world models can generate beautiful scenes.
Keeping those scenes alive for an hour without falling apart is the real challenge.
That's what caught my attention about LingBot-World 2.0 (LingBot-World-Infinity) from @robbyant_brain
Instead of chasing longer videos, it focuses on something much harder: persistent, interactive worlds that stay coherent while you explore.
A few highlights:
• Generates worlds from a single frame and continuously responds to live user actions through a causal world model.
• Streams stable 720p at 60 FPS in real time. The team reports a continuous 60 minute stress test across 20 different scenarios with no noticeable visual degradation.
• Uses a Brain-Cerebellum co-simulation framework where a VLM plans events while the video model turns them into consistent world evolution.
• Pilot and Director Agents help drive character behavior and introduce new objects and events.
• Open sourced with a 14B flagship model, while the paper also describes a lightweight 1.3B version for a single consumer GPU. There is also an online interactive demo.
The biggest takeaway?
We're moving beyond AI that generates clips.
We're getting closer to AI that generates living, evolving worlds you can actually interact with. And that feels like a much bigger shift than another jump in video quality.
Explore more:
💻 Github: github.com/Robbyant/lingbot-…
🤗 Weights: huggingface.co/collections/r…
🌐 Website-with videos you can use : technology.robbyant.com/ling…
🎮 Try it online: reactor.inc/lingbot-world-v2
#Robbyant #LingBot #WorldModel #EmbodiedAI #OpenSource #Robotics #ad
🤝 Paid partnership
For years we've accepted that launch videos require rebuilding the product you've already designed.
HyperFrames questions that assumption.
Sometimes the biggest innovation is simply removing unnecessary work.
github.com/heygen-com/hyperf…
🤝 Paid partnership
Knowledge is becoming software.
Not PDFs, courses, or ebooks.
Intelligent agents.
Boids helps creators turn expertise into products that keep serving users—and creating value—long after launch.
Everything changes.
🤝 Paid partnership
🚀 Meet Boids: boids.so/
Everyone should be able to turn their expertise into profit.
Boids helps creators turn their knowledge into agents in minutes, reach real users, and earn whenever those agents are used.
Your expertise scales.
Your data and knowledge stay protected.
Video editing has always been a bottleneck between having an idea and sharing it with the world.
Speech Cleanup removes a major piece of that bottleneck and makes publishing faster than ever. 🔥
🤝 Paid partnership