Jason C.
6.2K posts
Jason C.
@JasonCSJason
🎯Co-founder of https://t.co/1aXbYfuYZH (The AI Launchpad) | https://t.co/aULkIowz1R (1.5M Subscribers, TOP 1 AI Newsletter) | https://t.co/1Mx9fdUig1 (TOP 1 AI GTM Engine, $12M+ ARR)
→ Entrou em Mart 2018
777 Seguindo21.4K Seguidores
Stop the monopoly of the human mind.
Closed-source tech turns your brain into a product.
Human consciousness should never belong to corporations. @oall_global
#OpenBCIOpenSTC #Oall
Oall@oall_global
BCIs will go mainstream in 1-3 years. With it — a robot. Without it — a lower being. Even the president. No exceptions. OPEN-SOURCE is the only way out. Open BCI, Open STC. Fight for open BCI.
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@MiniMax_AI Dependability is the next frontier in AI. M2.7 prioritizes consistent performance. Trust becomes scalable.
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Jason C. retweetou
Introducing MiniMax-M2.7, our first model which deeply participated in its own evolution, with an 88% win-rate vs M2.5
- Production-Ready SWE: With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%), M2.7 reduced intervention-to-recovery time for online incidents to 3-min on certain occasions.
- Advanced Agentic Abilities: Trained for Agent Teams and tool search tool, with 97% skill adherence across 40+ complex skills. M2.7 is on par with Sonnet 4.6 in OpenClaw.
- Professional Workspace: SOTA in professional knowledge, supports multi-turn, high-fidelity Office file editing.
MiniMax Agent: agent.minimax.io
API: platform.minimax.io
Token Plan: platform.minimax.io/subscribe/toke…
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The line between assistant and teammate is fading. M2.7 contributes meaningfully to workflows. Collaboration becomes seamless.
MiniMax (official)@MiniMax_AI
Introducing MiniMax-M2.7, our first model which deeply participated in its own evolution, with an 88% win-rate vs M2.5 - Production-Ready SWE: With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%), M2.7 reduced intervention-to-recovery time for online incidents to 3-min on certain occasions. - Advanced Agentic Abilities: Trained for Agent Teams and tool search tool, with 97% skill adherence across 40+ complex skills. M2.7 is on par with Sonnet 4.6 in OpenClaw. - Professional Workspace: SOTA in professional knowledge, supports multi-turn, high-fidelity Office file editing. MiniMax Agent: agent.minimax.io API: platform.minimax.io Token Plan: platform.minimax.io/subscribe/toke…
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@dee_naliaks Agent builders know this pain.
Everything runs perfectly… until one tool call randomly fails and the entire pipeline dies.
Reliability matters more than intelligence for agents.😀
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Your AI gives wrong answers because it can't find the right info. Nobody makes content about this.
Nishkarsh@contextkingceo
We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️
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Dynamic Captions make every video feel more alive.
invideo makes that change simple and smooth.
Good text can turn a plain clip into something people want to keep watching.
Invideo@invideoOfficial
If your videos still have plain white subtitles in 2026, you're not serious about content. Dynamic Captions just went live on invideo - word-by-word animated text that actually looks cinematic. One click. Try Dynamic Captions on invideo.io
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Jason C. retweetou
🚨 GPT-5.4 just dropped — and MyClaw.ai is FIRST to ship KEY-FREE access.
No API key. No setup. Switch model → done.
But we're going bigger:
💰 $1M Token Subsidy Event
⚡️ GPT-5.4 at 50% OFF official pricing
⏰ 24 hours only
While others are still configuring API keys, MyClaw users are already running the new SOTA model at half price.
Built on @openclaw🦞 cc @steipete @AlexFinn
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GPT-5.4 is live. MyClaw users? Zero setup, zero keys, straight to the new SOTA. Grab the $1M Token Subsidy — 50% off for 24 hours only. Don't sleep on this.
Leo Ye@LeoYe_AI
🚨 GPT-5.4 just dropped — and MyClaw.ai is FIRST to ship KEY-FREE access. No API key. No setup. Switch model → done. But we're going bigger: 💰 $1M Token Subsidy Event ⚡️ GPT-5.4 at 50% OFF official pricing ⏰ 24 hours only While others are still configuring API keys, MyClaw users are already running the new SOTA model at half price. Built on @openclaw🦞 cc @steipete @AlexFinn
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Wondering if there is still a coder who doesn't use AI at all.
I simply can't imagine that.
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Jason C. retweetou
MiniMax M2.5 > Claude Opus 4.6
I have been using it for a couple of days and have never hit the limit.
I am currently on the Coding Plus plan which gives me 300 prompts per 5 hours.
My new setup is OpenCode + MiniMax M2.5
What I have noticed:
M2.5
– handles multi-step coding workflows and repo-level reasoning more reliably
– better at chaining actions. think: generate test, fix bug, refactor, repeat
– high TPS throughput
M2.5 hits ~80%+ on SWE-Bench coding benchmarks on par with Opus and runs these tasks 37% faster than its predecessor while costing ~1/10th - 1/20th the price.
Check out the video.
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"MiniMax M2.5 > Claude Opus 4.6" — take my upvote and my API credits 😂 Who's building agents with this beast?
Pratham@Prathkum
MiniMax M2.5 > Claude Opus 4.6 I have been using it for a couple of days and have never hit the limit. I am currently on the Coding Plus plan which gives me 300 prompts per 5 hours. My new setup is OpenCode + MiniMax M2.5 What I have noticed: M2.5 – handles multi-step coding workflows and repo-level reasoning more reliably – better at chaining actions. think: generate test, fix bug, refactor, repeat – high TPS throughput M2.5 hits ~80%+ on SWE-Bench coding benchmarks on par with Opus and runs these tasks 37% faster than its predecessor while costing ~1/10th - 1/20th the price. Check out the video.
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Unpopular opinion:
Your GitHub star count doesn't matter; your ability to solve real problems does.
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