Full-time Python Engineer - Sharing daily insights on Python, ML and AI. - DM/[email protected] for collaboration - Open for opportunities

Remote
Joined July 2022
Chat models generate messages. Decision models make decisions. Workflow models execute entire workflows in a single API call. Meet @TypeLLM the workflow model
Chat models generate messages. Decision models make decisions. Workflow models execute entire workflows in a single API call. Stop writing orchestration loops around your LLM. TypeLLM is a workflow model. You declare the decisions, their types and what depends on what. It runs the whole graph in ONE API call. Think SQL for AI workflows. Support ticket example: → Classify category + urgency in parallel → Refund only runs if billing → Reply reads category + urgency Four steps. One call. Typed results. vs four serial calls: → 2.1x fewer input tokens → ~1.9x faster
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Python Space retweeted
Don't waste your time, just use graphify skill to turn your codebase into an interactive map. Now available to all @perplexity_ai Computer users for FREE.
The Graphify skill by @graphify is now in Computer's skills marketplace, available to all Computer users. Turn a codebase into an interactive map of its files, functions, and dependencies. Tasks that use /graphify are free through October 31, up to 5,000 credits per user.
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Don't waste your time, just use graphify skill to turn your codebase into an interactive map. Now available to all @perplexity_ai Computer users for FREE.
The Graphify skill by @graphify is now in Computer's skills marketplace, available to all Computer users. Turn a codebase into an interactive map of its files, functions, and dependencies. Tasks that use /graphify are free through October 31, up to 5,000 credits per user.
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Python Space retweeted
AI tools are everywhere, but direct access to Seedance on Dreamina for $0.29 definitely caught my attention. Register through my official partner link to get the offer: dreamina.capcut.com/pricing/… #DreaminaOnly29Cents #Dreamina #DreaminaPartner #Seedance
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AI tools are everywhere, but direct access to Seedance on Dreamina for $0.29 definitely caught my attention. Register through my official partner link to get the offer: dreamina.capcut.com/pricing/… #DreaminaOnly29Cents #Dreamina #DreaminaPartner #Seedance
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Python Space retweeted
Now you can run Perplexity Computer fully local on your Mac! No wifi needed. works with Mac apps and 100% local. https://xitter.cf/t.co/z4KSTY1QrM @AravSrinivas
You can now run Perplexity Computer fully local on your Mac with no cloud based inference, without WiFi too. Enjoy!
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Python Space retweeted
Finally, Claude 5.5 meets Google Antigravity! Available in Antigravity 2.0, CLI, and IDEs
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Now you can run Perplexity Computer fully local on your Mac! No wifi needed. works with Mac apps and 100% local. https://xitter.cf/t.co/z4KSTY1QrM @AravSrinivas
You can now run Perplexity Computer fully local on your Mac with no cloud based inference, without WiFi too. Enjoy!
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Python Space retweeted
You're deep in a content draft when you remember a client needs a follow-up. You won't stop to open a reminders app. You'll tell yourself you'll remember. Then you don't. That's where SpeakON makes sense to me. Say it out loud, and the agent helps set the reminder. Voice Keyboard and Notes capture the thought. Agent helps you act on it. The useful part isn't voice typing. It's going from saying something to getting help with the next step, without breaking focus. For anyone juggling clients and content, that gap is where things slip.
we crushed a keyboard. its retirement party got a little out of hand. for years, it was there for every email, every plan, every “just one more thing.” a loyal colleague. a very loud colleague. but your ideas move faster than your fingers. and somewhere between knowing what you want to do and typing it all out, a quick task becomes another thing taking up your afternoon. meet SpeakON AI Agent. start with what you need, in your own words. less time behind a blinking cursor. more room to move things forward. the keyboard had a good run. now, let’s give your voice a turn. THE LAST KEYSTROKE is here. watch the film, then tell us: what’s the first task you’d hand over? speakon.app/x Disclaimer: The calling feature is still in beta and will be available soon. All other Agent features are available now, with ongoing improvements.
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You're deep in a content draft when you remember a client needs a follow-up. You won't stop to open a reminders app. You'll tell yourself you'll remember. Then you don't. That's where SpeakON makes sense to me. Say it out loud, and the agent helps set the reminder. Voice Keyboard and Notes capture the thought. Agent helps you act on it. The useful part isn't voice typing. It's going from saying something to getting help with the next step, without breaking focus. For anyone juggling clients and content, that gap is where things slip.
we crushed a keyboard. its retirement party got a little out of hand. for years, it was there for every email, every plan, every “just one more thing.” a loyal colleague. a very loud colleague. but your ideas move faster than your fingers. and somewhere between knowing what you want to do and typing it all out, a quick task becomes another thing taking up your afternoon. meet SpeakON AI Agent. start with what you need, in your own words. less time behind a blinking cursor. more room to move things forward. the keyboard had a good run. now, let’s give your voice a turn. THE LAST KEYSTROKE is here. watch the film, then tell us: what’s the first task you’d hand over? speakon.app/x Disclaimer: The calling feature is still in beta and will be available soon. All other Agent features are available now, with ongoing improvements.
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Python Space retweeted
The team behind Google's Gemini and Apple's MM-1 just released their first model. Meet Glimpse from @ElorianAI 👁️ Text models went superhuman at code. Images and video are still hard. Elorian is a whole lab built for Visual Thinking, and Glimpse is the first result. → Reasons over charts → Counts under trick conditions → Understands why a video clip is funny → Labels every subtask in robotics videos Free chat access. API is live.
Spent years watching models ace a single image and completely whiff on anything that moves or changes angle. Today we’re fixing that. Try Glimpse now, our first visual thinking model with competitive frontier performance compared to Astra on key public visual reasoning benchmarks.
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Python Space retweeted
This is not AI, but the incredible engineering efforts by @Tesla
Turns out the future does have flying cars
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This is not AI, but the incredible engineering efforts by @Tesla
Turns out the future does have flying cars
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Python Space retweeted
X is offering $5000 for posting 15 videos! Looks like X is coming for YouTube.
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X is offering $5000 for posting 15 videos! Looks like X is coming for YouTube.
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Python Space retweeted
Chat models generate messages. Decision models make decisions. Workflow models execute entire workflows in a single API call. Stop writing orchestration loops around your LLM. TypeLLM is a workflow model. You declare the decisions, their types and what depends on what. It runs the whole graph in ONE API call. Think SQL for AI workflows. Support ticket example: → Classify category + urgency in parallel → Refund only runs if billing → Reply reads category + urgency Four steps. One call. Typed results. vs four serial calls: → 2.1x fewer input tokens → ~1.9x faster
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Python Space retweeted
Now you can edit draw io diagrams inline in VS Code's Markdown Editor!
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Python Space retweeted
What to learn How do always-on, proactive agents work? Here is the great lecture at Stanford CS146S by @leerob
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Python Space retweeted
Chat models generate messages. Decision models make decisions. Workflow models execute entire workflows in a single API call. Meet @TypeLLM the workflow model
Chat models generate messages. Decision models make decisions. Workflow models execute entire workflows in a single API call. Stop writing orchestration loops around your LLM. TypeLLM is a workflow model. You declare the decisions, their types and what depends on what. It runs the whole graph in ONE API call. Think SQL for AI workflows. Support ticket example: → Classify category + urgency in parallel → Refund only runs if billing → Reply reads category + urgency Four steps. One call. Typed results. vs four serial calls: → 2.1x fewer input tokens → ~1.9x faster
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