elvis Profile picture
Dec 10, 2019 7 tweets 3 min read Read on X
Bin Yu discussing three principles of data science and interpretable machine learning. #NeurIPS2019 ImageImageImageImage
Can we mitigate data perturbations related issues Image
We need proper documentation about how we tried to come up with results... few things to consider: Image
We need to pay more attention to legitimate perturbations Image
P-values has been banned in some places but what can we do to address this issue? Image
A proposed way for inference Image
Some great references about interpretable machine learning ImageImage

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More from @omarsar0

Jan 8
Agents Overview

Great write-up on Agents by Chip.

Here are my takeaways: Image
🤖 Agents Overview

An AI agent is made up of both the environment it operates in (e.g., a game, the internet, or computer system) and the set of actions it can perform through its available tools. This dual definition is fundamental to understanding how agents work.
👨‍💻 Agent Example

The figure shows an example of an agent built on top of GPT-4. The environment is the computer which has access to a terminal and filesystem. The set of action include navigate, searching files, viewing files, etc. Image
Read 14 tweets
Jan 6
Google recently published this great whitepaper on Agents.

2025 is going to be a huge year for AI Agents.

Here's what's included:

- Introduction to AI Agents
- The role of tools in Agents
- Enhancing model performance with targeted learning
- Quick start to Agents with LangChain
- Production applications with Vertex AI Agents

Great place to start learning about AI Agents.Image
If you want to take it a step further, check out my new course on building AI Agents for different use cases: dair-ai.thinkific.com/courses/introd…
Read 13 tweets
Dec 17, 2024
Summary of today's OpenAI announcement (Day 9):

- o1 is launching out of preview in the API
- support for function calling, structured output, and developer messages
- reasoning_effort parameter to tell the model how much effort to spend on thinking
- vision inputs in the API is here too
Visual inputs with developer message (this is a new spin to system message for better steering the model) inside of the OpenAI Playground Image
Cool to see support for function calling and response format for o1 Image
Read 14 tweets
Dec 6, 2024
Summary of today's OpenAI announcement:

- introduces reinforcement fine-tuning (RFT) of o1
- tune o1 to learn to reason in new ways in custom domains
- RFT is better and more efficient than regular fine-tuning; needs just a few examples

1/n
How it looks in the dev platform. Examples show how to select RFT on o1-mini Image
What does data look like to use RFT. Uses a grader to grade the answer of the model. Different graders will be provided, with the ability to use custom grading. Image
Read 8 tweets
Jul 18, 2024
That's right! It's a huge week for small language models (SLMs)

Few new SLMs on my radar:
Mistral NeMo

Highlights:
- Introduced by Mistral + NVIDIA
- Apache 2.0 license
- outperforms Gemma 2 9B and Llama 2 8B
- multilingual capabilities
- efficient tokenizer (Tekken)

GPT-4o mini

Highlight: "15 cents per million input tokens, 60 cents per million output tokens, MMLU of 82%, and fast."

Read 7 tweets
Feb 21, 2024
JUST IN: Google DeepMind releases Gemma, a series of open models inspired by the same research and tech used for Gemini.

Open models fit various use cases so this is a very smart move from Google.

Great to see that Google recognizes the importance of openness in AI science and technology.

There are 2B (trained on 2T tokens) and 7B (trained on 6T tokens) models including base and instruction tuned versions. Trained on a context length of 8192 tokens.

Commercial use is allowed.

These are not multimodal models but based on the reported experimental results they appear to outperform Llama 2 7B and Mistral 7B.

I am excited about those MATH, HumanEval, GSM8K, and AGIEval results. These are really incredible results for a model this size.

Excited to dive deeper into these models. The model prompting guide is dropping soon. Stay tuned!Image
When I said outperforms other models, I meant generally outperforms them on all the benchmarks. Llama has a lot of catching up to do but it is interesting to see Mistral 7B trail Gemma very closely. These numbers don't really mean much in the context of real-world applications.

If you follow me here on X, you know how excited I get about unlocking unique value and use cases with small language models (SLMs). It will also be fun to run these locally and other other small devices. As I have been saying, SLMs are underexplored. It's a mistake to just see them as research artifacts.Image
Read 4 tweets

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