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Madison Kanna

@Madisonkanna • 83,951 subscribers

post-training & inference @FireworksAI_HQ https://t.co/fWhUnuouar https://t.co/cwiVhN1NpV

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Didn’t realize my dev diary from terminal tower was out ☠️

Didn’t realize my dev diary from terminal tower was out ☠️

148,488 просмотров

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I went to Miami to chat with dax, co-founder of OpenCode. We talked about the future of software engineering, coding agents, and why open source matters more now than ever. Timestamps: 0:00 Intro 5:30 Miami vs San Francisco tech scene 15:05 OpenCode origin story, scaling while open-source 25:03 OpenCode vs. Anthropic: owning models, open-source AI 33:36 AI hardware shortages, predicting the future 42:15 The bet of open-weight models, China vs. US 48:34 Why inference is hard, economics of intelligence 55:36 Will developers be automated? Software engineering as a craft 1:11:02 Advice to founders, building in public, marketing I had so much fun making this with Lan. Enjoy!

I went to Miami to chat with dax, co-founder of OpenCode. We talked about the future of software engineering, coding agents, and why open source matters more now than ever. Timestamps: 0:00 Intro 5:30 Miami vs San Francisco tech scene 15:05 OpenCode origin story, scaling while open-source 25:03 OpenCode vs. Anthropic: owning models, open-source AI 33:36 AI hardware shortages, predicting the future 42:15 The bet of open-weight models, China vs. US 48:34 Why inference is hard, economics of intelligence 55:36 Will developers be automated? Software engineering as a craft 1:11:02 Advice to founders, building in public, marketing I had so much fun making this with Lan. Enjoy!

271,922 просмотров • 3 месяцев назад

How to become an AI researcher with Charlie O'Neill Charlie co-founded Parsed to build specialized open-source models that can outperform frontier labs. I first met Charlie when Parsed was acquired by Baseten, and now he leads our model development team. Charlie is one of the smartest people I know, and I had the pleasure of talking to him about: 0:00 Intro 3:13 Leaving Oxford to start a company 6:37 Becoming an AI researcher 15:37 Developing a unique POV as your moat 22:04 Parsed origin story 26:01 Big Token, the case for open-source models 33:40 Post-training, fine-tuning, specialization 46:52 Will open models catch up with closed models? 51:50 AI-led job replacement vs job creation 54:45 How to get into inference engineering This is one of my favorite conversations I’ve had in a long time. Made with Lan behind the scenes. Enjoy!

How to become an AI researcher with Charlie O'Neill Charlie co-founded Parsed to build specialized open-source models that can outperform frontier labs. I first met Charlie when Parsed was acquired by Baseten, and now he leads our model development team. Charlie is one of the smartest people I know, and I had the pleasure of talking to him about: 0:00 Intro 3:13 Leaving Oxford to start a company 6:37 Becoming an AI researcher 15:37 Developing a unique POV as your moat 22:04 Parsed origin story 26:01 Big Token, the case for open-source models 33:40 Post-training, fine-tuning, specialization 46:52 Will open models catch up with closed models? 51:50 AI-led job replacement vs job creation 54:45 How to get into inference engineering This is one of my favorite conversations I’ve had in a long time. Made with Lan behind the scenes. Enjoy!

147,366 просмотров • 3 месяцев назад

How to pass technical interviews using a 4 step problem-solving method 👇

How to pass technical interviews using a 4 step problem-solving method 👇

751,889 просмотров • 3 лет назад

It’s true that you don’t need a CS degree to become a developer. But I’m starting to think we’ve undersold the importance of having a solid understanding of computer science if you want to be a great developer.

It’s true that you don’t need a CS degree to become a developer. But I’m starting to think we’ve undersold the importance of having a solid understanding of computer science if you want to be a great developer.

710,908 просмотров • 2 лет назад

Big day for American open-source AI. For the launch of Laguna S, I sat down with Eiso Kant to discuss its architecture, the economics of open weights, and the question of who gets to build intelligence. Timestamps: 0:00 Intro 1:50 Why Poolside started opening its models: the oligopoly on intelligence 4:28 Getting nerd-sniped by Karpathy, building LLMs before anyone cared 11:20 Laguna S: 118B parameters, 8B active, built in 8 weeks 13:05 The future of software engineering: behaviors over IQ 14:25 Sliding window attention, 1M context, the model factory 15:50 Being an American open-source lab 20:47 The economics of open weights 24:22 Who gets to build intelligence? The 12–18 month window 30:28 Erdős 397 in 30 minutes 31:48 Extracting transcripts with a debugger Congrats to the Poolside team on the launch!

Big day for American open-source AI. For the launch of Laguna S, I sat down with Eiso Kant to discuss its architecture, the economics of open weights, and the question of who gets to build intelligence. Timestamps: 0:00 Intro 1:50 Why Poolside started opening its models: the oligopoly on intelligence 4:28 Getting nerd-sniped by Karpathy, building LLMs before anyone cared 11:20 Laguna S: 118B parameters, 8B active, built in 8 weeks 13:05 The future of software engineering: behaviors over IQ 14:25 Sliding window attention, 1M context, the model factory 15:50 Being an American open-source lab 20:47 The economics of open weights 24:22 Who gets to build intelligence? The 12–18 month window 30:28 Erdős 397 in 30 minutes 31:48 Extracting transcripts with a debugger Congrats to the Poolside team on the launch!

64,611 просмотров • 3 месяцев назад

People assume the demand for inference will grow linearly with user adoption. However, the demand is actually growing combinatorially. Here’s why from researcher and head of training at Baseten Charlie O'Neill

People assume the demand for inference will grow linearly with user adoption. However, the demand is actually growing combinatorially. Here’s why from researcher and head of training at Baseten Charlie O'Neill

117,489 просмотров • 6 месяцев назад

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

What is AI inference engineering, why is it such an in-demand skill, and how do you break into the field? With author of Inference Engineering Philip Kiely and head of training at Baseten Charlie O'Neill 0:00: What is inference? 2:47: History of inference 4:59: Downstream effects of AI research on inference 13:54: What you'll learn from Inference Engineering 16:14: Advice for engineers transitioning into AI 19:00: Open source models driving inference growth 20:55: Specialization vs. frontier closed models 23:51: "Big Token" and the importance of open source AI 27:18: Where to get Inference Engineering

119,268 просмотров • 6 месяцев назад

Does San Francisco smell? dax and I disagree. Putting together a taskforce to investigate.

Does San Francisco smell? dax and I disagree. Putting together a taskforce to investigate.

66,072 просмотров • 3 месяцев назад

After his talk Lan and I managed to grab Thariq to chat about about token maxxing, Fable, and technical writing

After his talk Lan and I managed to grab Thariq to chat about about token maxxing, Fable, and technical writing

33,638 просмотров • 3 месяцев назад

At AIE last week, Lan and I caught up with our friend Kate Deyneka, former ML engineer at Snapchat, about the newest models, building in public and her new app Reelful

At AIE last week, Lan and I caught up with our friend Kate Deyneka, former ML engineer at Snapchat, about the newest models, building in public and her new app Reelful

21,008 просмотров • 3 месяцев назад

With the launch of GLM 5.2 this week, I see everyone asking "have open models caught up to closed models?" The more interesting question that's getting missed: what can you do with an open model that you can't do with a closed one? You can specialize them. And when you do, the number of economically valuable tasks open models can do actually subsumes that of closed models. Charlie O'Neill explaining this:

With the launch of GLM 5.2 this week, I see everyone asking "have open models caught up to closed models?" The more interesting question that's getting missed: what can you do with an open model that you can't do with a closed one? You can specialize them. And when you do, the number of economically valuable tasks open models can do actually subsumes that of closed models. Charlie O'Neill explaining this:

18,149 просмотров • 3 месяцев назад

Matthew McConaughey on why you should learn vim

Matthew McConaughey on why you should learn vim

27,854 просмотров • 1 год назад

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