Technical Insights
From Optimizing for People to Optimizing for Machines: Why large language models are increasingly fine-tuned to fit into agentic workflows
Large language models (LLMs) are typically optimized to answer peoples’ questions.
Technical Insights
How to Get User Feedback to Your AI Products - Fast!: Your ability to prototype AI capabilities fast affects all parts of the product development cycle, starting with getting user feedback.
Startups live or die by their ability to execute at speed. For large companies, too, the speed with which an innovation team is able to iterate has a huge impact on its odds of success.
Technical Insights
How to Get User Feedback to Your AI Products - Fast!: Your ability to prototype AI capabilities fast affects all parts of the product development cycle, starting with getting user feedback.
Startups live or die by their ability to execute at speed. For large companies, too, the speed with which an innovation team is able to iterate has a huge impact on its odds of success.
Technical Insights
Why Science-Fiction Scenarios of AI’s Emergent Behavior Are Likely to Remain Fictional: The sudden apparance of “emergent” AI capabilities may be an artifact of the metrics you study
Over the weekend, my two kids colluded in a hilariously bad attempt to mislead me to look in the wrong place during a game of hide-and-seek.
Technical Insights
Why Science-Fiction Scenarios of AI’s Emergent Behavior Are Likely to Remain Fictional: The sudden apparance of “emergent” AI capabilities may be an artifact of the metrics you study
Over the weekend, my two kids colluded in a hilariously bad attempt to mislead me to look in the wrong place during a game of hide-and-seek.
Technical Insights
Welcoming Diverse Approaches Keeps Machine Learning Strong: What technology counts as an “agent”? Instead of arguing, let's consider a spectrum along which various technologies are “agentic.”
One reason for machine learning’s success is that our field welcomes a wide range of work.
Technical Insights
Welcoming Diverse Approaches Keeps Machine Learning Strong: What technology counts as an “agent”? Instead of arguing, let's consider a spectrum along which various technologies are “agentic.”
One reason for machine learning’s success is that our field welcomes a wide range of work.
Technical Insights
We Need Better Evals for LLM Applications: It’s hard to evaluate AI applications built on large language models. Better evals would accelerate progress.
A barrier to faster progress in generative AI is evaluations (evals), particularly of custom AI applications that generate free-form text.
Technical Insights
We Need Better Evals for LLM Applications: It’s hard to evaluate AI applications built on large language models. Better evals would accelerate progress.
A barrier to faster progress in generative AI is evaluations (evals), particularly of custom AI applications that generate free-form text.
Technical Insights
Project Idea — A Car for Dinosaurs: AI projects don’t need to have a meaningful deliverable. Lower the bar and do something creative.
A good way to get started in AI is to start with coursework, which gives a systematic way to gain knowledge, and then to work on projects.
Technical Insights
Project Idea — A Car for Dinosaurs: AI projects don’t need to have a meaningful deliverable. Lower the bar and do something creative.
A good way to get started in AI is to start with coursework, which gives a systematic way to gain knowledge, and then to work on projects.
Technical Insights
From Prompts to Mega-Prompts: Best practices for developers of LLM-based applications in the era of long context and faster, cheaper token generation
In the last couple of days, Google announced a doubling of Gemini Pro 1.5's input context window from 1 million to 2 million tokens, and OpenAI released GPT-4o, which generates tokens 2x faster and 50% cheaper than GPT-4 Turbo and natively accepts and generates multimodal tokens.
Technical Insights
From Prompts to Mega-Prompts: Best practices for developers of LLM-based applications in the era of long context and faster, cheaper token generation
In the last couple of days, Google announced a doubling of Gemini Pro 1.5's input context window from 1 million to 2 million tokens, and OpenAI released GPT-4o, which generates tokens 2x faster and 50% cheaper than GPT-4 Turbo and natively accepts and generates multimodal tokens.
Technical Insights
Building Models That Learn From Themselves: AI developers are hungry for more high-quality training data. The combination of agentic workflows and inexpensive token generation could supply it.
Inexpensive token generation and agentic workflows for large language models (LLMs) open up intriguing new possibilities for training LLMs on synthetic data. Pretraining an LLM
Technical Insights
Building Models That Learn From Themselves: AI developers are hungry for more high-quality training data. The combination of agentic workflows and inexpensive token generation could supply it.
Inexpensive token generation and agentic workflows for large language models (LLMs) open up intriguing new possibilities for training LLMs on synthetic data. Pretraining an LLM
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