LLMs
Disruptive innovation comes in two flavors: (1) New-market disruption, where the company creates and claims a new segment in an existing market by catering to an underserved customer base, or (2) Low-end disruption, in which a company uses a low-cost business model to enter at the bottom of an existing market and claim a segment.
Copilots don’t... See more
Copilots don’t... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
- Mistral AI shows a promising alternative to the GPT 3.5 model using prompt engineering .
- Mistral AI can be used where it requires high volume and faster processing time with very little cost .
- Mistral AI can be used as pre-filtering to GPT 4 to reduce cost i.e. can be used to filter down search results .
Mistral 7B is 187x cheaper compared to GPT-4
TorchMultimodal (Beta Release)
Introduction
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. It provides:
Introduction
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale. It provides:
- A repository of modular and composable building blocks (models, fusion layers, loss functions, datasets and utilities).
- A repository of examples that show how to combine these building
facebookresearch • GitHub - facebookresearch/multimodal at a33a8b888a542a4578b16972aecd072eff02c1a6
We went to OpenAI's office in San Francisco yesterday to ask them all the questions we had on Quivr (YC W24), here is what we learned:
1. Their office is super nice & you can eat damn good croissant in SF!
2. We can expect GPT 3.5 & 4 price to keep going down
3. A lot of people are using the Assistants API to build their use cases
4. It costs 2M$ to... See more
1. Their office is super nice & you can eat damn good croissant in SF!
2. We can expect GPT 3.5 & 4 price to keep going down
3. A lot of people are using the Assistants API to build their use cases
4. It costs 2M$ to... See more
Paul Venuto • feed updates
core components of Deep RL that enabled success like AlphaGo: self-play and look-ahead planning.
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
These two components might be some of the most important ideas to improve all of AI.
In addition to using our built-in capabilities, you can also define custom actions by making one or more APIs available to the GPT. Like plugins, actions allow GPTs to integrate external data or interact with the real-world. Connect GPTs to databases, plug them into emails, or make them your shopping assistant. For example, you could integrate a... See more
Introducing GPTs
- Self-play is the idea that an agent can improve its gameplay by playing against slightly different versions of itself because it’ll progressively encounter more challenging situations. In the space of LLMs, it is almost certain that the largest portion of self-play will look like AI Feedback rather than competitive processes.
Nathan Lambert • The Q* hypothesis: Tree-of-thoughts reasoning, process reward models, and supercharging synthetic data
How do models represent style, and how can we more precisely extract and steer it?
A commonly requested feature in almost any LLM-based writing application is “I want the AI to respond in my style of writing,” or “I want the AI to adhere to this style guide.” Aside from costly and complicated multi-stage finetuning processes like Anthropic’s RL with... See more
A commonly requested feature in almost any LLM-based writing application is “I want the AI to respond in my style of writing,” or “I want the AI to adhere to this style guide.” Aside from costly and complicated multi-stage finetuning processes like Anthropic’s RL with... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
You can think your way into solving a deterministic system, but you cannot think your way into solving a probabilistic system.
The first thing that I want to call out is that deterministic software has edge cases, while probabilistic software has long tails.
I find that a lot of junior folks try to really think hard about edge cases around... See more