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The AI Colony
@TheAIColony
Home of everything AI — Here to help you use Al to boost your productivity — Daily insights on AI tools & tips || DM for collaborations hello@theaicolony.com
8.7K Following    230.1K Followers
Polsia just dropped a film where the AI holds the camera and its own founder is the subject.  Ben Cera walks back in with a suitcase while the AI logs him like a security file, marking him "returned" with 12 badges earned.  This is what it looks like when the software running the company starts watching the boss. See the full film here:
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I hired a team of eleven. He is still a solo founder. Ask him. Log entry two
Huawei’s foldable‑screen laptop is so cool.
The model finishes training. The world keeps changing. That gap is where Boltzbit is building. Imagine an enterprise agent trained before a company changes its return policy. A static model needs the new rule added to every prompt or waits for another training cycle. Boltzbit’s Bayesian Self-learning Transformers (BAST) instead turn live data into targeted weight updates, allowing the model to incorporate the new policy after deployment. The next great model might not be the one that knew the most on launch day. It might be the one that never stopped learning. See how the architecture works:
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We’ve just released the preview version of our latest paper: Infinite-Parameter LLMs — Generating and Adapting Weights from Live Data. In it, we demonstrate that large language models can learn up to 1,000x faster through Bayesian Self-learning transformers (BAST) than SOTA training algorithms engineered by human researchers. This breakthrough marks a critical shift in AI research, from cost-intensive, static-weight AI to energy-efficient, dynamic-weight AI. For a decade, building more advanced models has been achieved by training bigger ones on more data. This approach is now hitting a ceiling with the supply of pretraining text projected to run out in the next two to five years. Meanwhile, the fast adoption of AI agents is producing an unprecedented amount of continuously-growing data that models can learn from. None of it is captured, locked in individual sessions and lost as soon as the agent completes the task. Bringing self-learning AI agents to users captures the value of that data. We validated that BAST LLMs overcome the fundamental limitations of memory-based learning, such as Retrieval-Augmented Generation (RAG), in both cost and performance, across long-context conversations. Without underlying architectural innovation like BAST, RAG, larger context windows, and agent scaffolding suffer a drop in performance and escalating input token cost due to the static weight of LLMs. This research underscores a fundamental premise of our work at Boltzbit to achieve General Learning Intelligence and democratise model ownership. Scaling up static-weight model size or layering on more workarounds cannot address the spiraling cost of training AI systems. The viable path is a new AI architecture that adapts its own weights. Preview version of the paper:
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Agents can create PRs in minutes, but understanding them still takes work. CodeRabbit Change Stack connects a PR's purpose, behavior, dependencies, and code so reviewers can really verify it before approving. Do you understand what you're about to merge?
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Two new open-source models from NetEase Youdao just hit #1# on @huggingface Trending in their categories: → Confucius4-R2T2 - ASR → Confucius4-T3PO - Translation What caught my attention isn’t just the ranking. It’s what they enable when you put them together: a fully open-source real-time voice/interpretation stack.
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Tested Xiaomi's new MiMo V2.6 Pro before its official launch. #1# open-source model on Artificial Analysis's Intelligence Index, at $0.13/ task. Thread on what actually stood out :
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Everyone is trying to build smarter AI agents. I think they're solving the wrong problem. What caught my attention about WorkSwarm from openJiuwen isn't that it makes one agent smarter. It's that it focuses on helping teams of agents coordinate over long-running tasks without losing context, ownership, or decisions. It's open source under Apache 2.0.
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Most AI agents are optimized to complete a task. openJiuwen's WorkSwarm is pushing toward something more ambitious: agents that improve themselves through real work. Three things that make it different 👇 1.⁠ ⁠Dual-Dimension RSI A continuous self-improvement loop — Evaluate → Analyze → Propose → Execute → Adopt — that improves both how the agent works (prompts, skills, tools) and what it delivers (papers, code, artifacts). 2.⁠ ⁠Persistent Sessions Keeps roles, decisions, and boundaries intact across hundreds of turns. In one test: 5 people, 189 turns, 8/8 cross-role conflicts caught. 3.⁠ ⁠Compute Affinity Optimizes resource usage — 22.8% lower HBM peak, 14.36% higher KV cache hit rate — making repeated optimization more efficient. Open source under Apache 2.0. GitHub 👉 #AI# #Agent# #openJiuwen# #WorkSwarm#
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We've raised a $143M Series C at a $1.5B valuation. In 2023 we spent our time arguing that AI code needed its own reviewer. That argument is over. The work now is moving into the change itself. This is where we think Agentic Change Management comes in.
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We raised a $143M Series C at a $1.5B valuation to build the control layer for software change. Our first investor got involved for a totally different reason.
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4 FREE SEEDANCE 2.5 GENERATIONS ON DREAMINA for users in USA. Queue-FREE. Full SPEED, always. 3 days only. Same resolution, same clip length, converted to per-second. Checked today. One of these is not like the others. A 10-second Seedance 2.5 clip for $0.97. A 20-second clip for $1.94. A full 30 seconds for $2.91. Plus, the LOWEST PRICE applies wherever you are. Check the banner on the website 👉 #Dreamina# #DreaminaPartner# #Seedance25#
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Every agentic dev tool this year has been racing to write code faster. But talk to anyone running agents daily and the real cost is what comes after, the reviewing, the checking, the "wait, did this break checkout?" Coldtea's bet is that QA agents and monitoring agents belong in the same environment as the coding agent. The whole lifecycle, not just the typing. That's the right problem to be working on.
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Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. @ColdteaAI brings your coding agents, agentic end-to-end testing, and production monitoring agents into ONE development environment, so you can move at agent speed without breaking anything.
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Twelve days of announcements just ended. The part that matters starts now. @invideoOfficial Agent Two is live, built over months by engineers and filmmakers, running the same platform Fortune 500s, global agencies and film studios use for real client work. Invideo spent 12 days showing what they built. You get 365 to show what you made with it.
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Day 12 of 12 Days of Agent Two. Months of work by engineers and filmmakers, all leading here. The same platform Fortune 500s, global agencies, and film studios use is now in your hands. These 12 days were never about what we built. They're about what you'll make with it.
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Don't fall for "unlimited" hype. Dreamina offers zero-queue access and the lowest Seedance 2.5 price at $0.097/sec (annual). Queued 4 Seedance 2.5 generations at once. All 4 back before my coffee went cold. Still that fast on day 30 — no throttling, no priority tier to buy. #dreamina# #dreaminapartner# #dreamina25# #seedance#
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The model was never the moat. @invideoOfficial just explained why Agent Two beats raw frontier models at creative work. They plug in every state of the art model, then wrap it in a harness built from real creative research that decides how each one gets used. Same models. 4x faster. Half the price.
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Today is Day 11 of 12 Days of Agent Two. Agent Two isn't just Claude under the hood - we get asked this a lot. The truth is - while we use all the state of the art models out there, the Agent's real intelligence comes from its harness: a domain-specific layer built from continuous creative research that shapes how every model is actually used - more about this in the video. But this harness is what makes Agent Two frontier intelligence for creative work - at 4x the speed, and half the price.
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The demos looked easy. Then people tried it themselves and watched the agent rebuild the same 3D model four times in one afternoon. That's the gap nobody was talking about. Tesana's LOOP closes it by standardising the parts that kept getting regenerated. Assets, libraries, multiplayer, all inside one run.
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Lot's of noise recently about Gauntlet Loop after @mattshumer_ game example - but truth is most agent loops without standardised frameworks around game libraries, 3D models, textures, terrain, lighting and multiplayer turn out to be super unpredictable, messy, overly expensive, as @levelsio pointed out Today we're introducing LOOP - our take on agent loops to build AI games. The Tesana LOOP inside our AI game engine solves assets → game libraries → multiplayer → and a full user-facing experience. Set a budget for your LOOP, and come back to a properly finished game ready to launch, without reinventing and wasting tokens on your build every session.
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Lot's of noise recently about Gauntlet Loop after @mattshumer_ game example - but truth is most agent loops without standardised frameworks around game libraries, 3D models, textures, terrain, lighting and multiplayer turn out to be super unpredictable, messy, overly expensive, as @levelsio pointed out Today we're introducing LOOP - our take on agent loops to build AI games. The Tesana LOOP inside our AI game engine solves assets → game libraries → multiplayer → and a full user-facing experience. Set a budget for your LOOP, and come back to a properly finished game ready to launch, without reinventing and wasting tokens on your build every session.
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AI tools are moving from “give me a prompt” to “give me the job.” @invideoOfficial Agent Two workflows are where things start getting really interesting.
Launching Workflows on Agent Two. Day 10 of 12 Days of Agent Two. Instead of briefing the agent through every step yourself, workflows take you on a guided run. You answer a few questions, upload some references, pick between options, and come out the other side with the job done. We're launching with 9 workflows across filmmaking and marketing, and you can also build your own and reuse them across any project. Tell us in the comments what workflow you want us to build next. The most liked one gets made. Agent Two is frontier intelligence for creative work. 4x faster, at half the price.
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When the biggest players start following the roadmap, you know the small team was onto something. @wanderboat_ai
Twice in one year, Wanderboat features have shown up in Google Maps. March: Chat feeds + Vibe Checking Today: AI Food Ordering, Hotels, Local Events... Their "biggest transformation in over a decade" is still a demo video (with a "simulated" disclaimer). Ours has been live for 1.5 years. Feels like Wanderboat has been handing them a free roadmap. And we have more.
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You don't have to second-guess every generation anymore. That's the part that stood out to us. @TopviewAIhq's Ultra Annual gives you 365 days of unlimited Wan 3.0, 60 days of unlimited Seedance 2.5, and Seedance from just $0.12/sec. The less time you spend thinking about credits, the more time you spend finding better ideas.
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Topview’s Ultra Annual offer is bigger than ever. 🔥 60 days unlimited Seedance 2.5. 365 days unlimited Wan 3.0. 2 of the latest AI video models, unlocked for more creation. What's more? Seedance 2.5 from only $0.12/sec. It can't get any better than this. More models. More generations. More room to create. #TopviewAI# #AIVideo# #AIFilmmaking# #AIStorytelling#
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