#153 - Taylor Swift Deepfakes, ChatGPT features, Meta-Prompting, two new US bills
Feb 4, 2024
auto_awesome
Topics discussed include Taylor Swift deepfakes, AI-generated videos, Microsoft's updates to AI tools, competition between ChatGPT and Google Bard, AI integrations in web browsers, Baidu's AI chatbot powering Samsung's new smartphones, drop in market cap for AI companies, Hugging Face and Google collaboration, Alpha Codeium as an open-source code generation model, efficiency of vision transformers compared to biological systems, prevalence of AI-generated content on the internet, and the introduction of a bill to criminalize non-consensual AI images.
Advancements in AI algorithms have led to more versatile and capable models with increased world knowledge.
Speculative sampling is a technique that allows for more creative and diverse outputs from large language models.
Vision transformers show surprisingly similar performance to newborn chicks in recognizing and distinguishing objects, suggesting the efficiency of biological visual systems can be approximated by AI models.
Deep dives
Alpha Codeium: A Specialized Model for Coding
Alpha Codeium is an open-source model that specializes in coding and has shown significant improvement over general language models. It uses flow engineering, a technique that generates code with iteration and ensures code integrity. The model scores higher on coding benchmarks compared to other models and has outperformed GPT 4. It provides a more specific and focused approach to coding tasks.
Meta Prompting: Enhancing Language Models with Task-Agnostic Scaffolding
The Meta Prompting paper introduces a new approach to balancing generality and specificity in language models. Instead of manually designing specific prompts, the model itself generates prompts through a meta model. This approach enables the model to break down tasks, assign them to specialized models, and apply critical thinking to combine their results. This method enhances the strengths of both general and specialist models, improving the overall performance and flexibility of language models.
Deep Seek Coder: A Specialized Model for Programming
Deep Seek Coder is a large language model designed for programming tasks. It specializes in coding and offers improved performance compared to previous models like GPT 3.5. The model has been trained on a vast amount of code-related data. While it may not match the performance of GPT 4, Deep Seek Coder demonstrates state-of-the-art capabilities in generating code and provides useful support for developers and programmers.
Increasing General Purpose Models with More World Knowledge
The podcast episode discusses how recent advancements in AI algorithms, such as GPT-3, have led to more general purpose models with increased world knowledge. These models can now reason sensibly and rely on their world knowledge during the inference stage. The podcast highlights the journey towards developing more versatile and capable models.
Speculative Sampling to Improve Output Generation
The podcast explores the concept of speculative sampling, a new technique for generating output from large language models. Speculative sampling involves exploring different possible continuations or predictions at each step of the text generation process and sampling from those variations. This approach allows for more creative and diverse outputs, and research shows that it can significantly speed up output generation compared to traditional decoding methods.
Comparing Vision Transformers to Newborn Visual Systems
The podcast episode delves into a study that compares the efficiency of vision transformers, a type of deep learning model used in computer vision, to newborn visual systems. The study finds surprisingly similar performance between vision transformers and newborn chicks in recognizing and distinguishing objects from different perspectives. This suggests that vision transformers can approximate the efficiency of biological visual systems and opens up possibilities for further exploration in AI and neuroscience.
Our 153rd episode with a summary and discussion of last week's big AI news!
Check out our sponsor, the SuperDataScience podcast. You can listen to SDS across all major podcasting platforms (e.g., Spotify, Apple Podcasts, Google Podcasts) plus there’s a video version on YouTube.