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thiago
13.3K posts

thiago
@dooart
mais ou menos são nas horas vagas
São Paulo, Brazil Katılım Temmuz 2007
248 Takip Edilen4.5K Takipçiler

@clarkbw @neondatabase this is awesome! how easy is it to migrate a project from @supabase to @neondatabase? i just realized neon has alll the features i need like auth and branching
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New @neondatabase Scale plan gives you SOC 2 support for pay-as-you-go ($5 min, scale compute)
SOC 2 is a standard for running SaaS businesses, you shouldn't be paying $599 / month in fees to access it

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@levelsio @featurebase i remember you recommended canny a while back bc in theory it managed itself, but seems like you moved on to featurebase - curious to learn why if you don't mind sharing
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Another bug submitted by a user, that I just copy pasted into Cursor and then immediately fixed
I think I need to create an automated workflow that pulls bugs reported from my @featurebase bug board, then sends them into Cursor/AI etc, to immediately fix it, then do a pull request that I can then check
Fully automated AI bug fixing workflow will be the standard I think
And then my daily work will just be checking the AI's pull requests and approve or reject



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@FireworksAI_HQ this is awesome!
do you include the cot tokens in the final output costs? or just charging for the literal output
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🚀 𝗗𝗲𝗲𝗽𝗦𝗲𝗲𝗸 𝗥𝟭 𝗡𝗼𝘄 𝗟𝗶𝘃𝗲 𝗼𝗻 𝗙𝗶𝗿𝗲𝘄𝗼𝗿𝗸𝘀❗
DeepSeek R1, a new best in class reasoning model, is now available on Fireworks Serverless, On-Demand and Enterprise, with reasoning quality comparable to OpenAI's o1 model.
This is an early release - we expect improvements in performance and speed soon!
DeepSeek R1 is a new best in class for reasoning models, comparable to o1
🥇SOTA open model: Comparable to OpenAI-o1 across math, code, and reasoning tasks
🧠671B MoE parameters with 37B activated parameters, trained with Reinforcement Learning
🔑Distillation with R1: DeepSeek R1 has transparent thinking tokens, and is released under the MIT License, allowing training and tuning of models through distillation of R1 outputs
🔓A family of open models: DeepSeek has released R1, R1-Zero, and six dense models distilled from DeepSeek-R1 based on Llama and Qwen models
Congrats to the @deepseek_ai team for this release and pushing the boundaries of what's possible in open models!
DeepSeek R1 on Fireworks:
📜Enabled with the full 160K context window
⚡Available now on Serverless, On-Demand or Enterprise deployments
🎤Talk to use on how to distil from R1 or use R1 directly for enterprise / production use cases
Try DeepSeek R1 now in our playground or via API. Enterprise customers, let's talk about how you can best use DeepSeek R1 for your use cases👇

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@height_app hey! is it still possible to use height v1? i'm sure some some teams will love v2 but it's way too complicated for me. i loved v1 for its simplicity
ironically i was about to pitch height as a linear replacement to my team because i wanted something simpler 🙈
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