2/ Debug Code Prompt: You are a debugging expert with over 20 years of experience. Analyze the provided [PIECE OF CODE] to identify and fix a specific [ERROR]. 1. Step through the code to diagnose the issue. 2. Propose a solution to
LLMS
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10 Prompts to Improve Your Workflow with Claude
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Claude is an underrated coding assistant. But 99% of devs aren’t using it effectively. Here are 10 prompts to change that:
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NLP Hype vs Reality: Expert Discussion on Stochastic Parrots
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He can also talk to you about hype VS reality in natural language processing (check out this AI Hype VS Reality session we held as part of Stochastic Parrots Day in 2023: https://
peertube.dair-institute.org/w/p/5k7JempgUb
CAcpTjUZPuKQ?playlistPosition=3&resume=true
… More at https://
dair-institute.org/stochastic-par
rots-day/
… -
Symbolic Rules as Critical LLM Training Components
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or, putting it differently, that set of weights, if you don’t have the system, and just the trained LLM, is the OUTPUT of a system as a whole that used symbolic rules as a critical component in its training process.
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DeepSeek R1 Innovation: Beyond LLM Architecture Apparatus
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also, the community note depends on ignoring the RL apparatus of DeepSeek, and treating R1 as the LLM only, ignoring that apparatus, but that apparatus was part of the innovation, which is why it was reported in the paper. so yes you can play definitional games if you like but
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Smaller AI models drive down intelligence costs across industries
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Some key takeaways: 1. AI’s rapidly improving capabilities mean that the cost of reasoning and intelligence is dropping. This opens up opportunities to integrate smarter, smaller models into products. Whether you’re building for health care, education, or another industry, think
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Karina Nguyen leads AI research at OpenAI advancing language models
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Karina Nguyen (@karinanguyen_) leads a research team at @OpenAI, where she’s been pivotal in developing Canvas, Tasks, and the o1 language model. Prior to OpenAI, Karina was at @Anthropic, where she led post-training and evaluation work for Claude 3 models, and contributed to… pic.twitter.com/8kMbXv97yt
— Lenny Rachitsky (@lennysan) 9 février 2025Karina Nguyen (
@karinanguyen
) leads a research team at @OpenAI
, where she’s been pivotal in developing Canvas, Tasks, and the o1 language model. Prior to OpenAI, Karina was at @Anthropic
, where she led post-training and evaluation work for Claude 3 models, and contributed to -
The Evolution of AI from Assistive Tools to Autonomous Agents
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1/ AI is no longer just an assistive tool—it’s evolving into an agent. Imagine a software engineer AI that can work like a junior developer. Now imagine a million of them, across every industry.
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Scaling Laws and the Economics of AI Compute
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AI gets smarter as you spend more on compute, data & training. Progress is predictable and scaling laws hold up. AI costs are dropping 10x every year, making it more accessible than ever. Compare that to Moore’s Law, which only doubled computing power every 18 months.
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Text Data Augmentation Techniques for Large Language Models
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10). Survey: Text Data Augmentation for LLMs This comprehensive survey covers text data augmentation techniques for LLMs.