Research exploring the capabilities of artificial intelligence (AI) to try and interpret and translate brain activity has been popping up more and more lately.
By using neuroimaging data and AI models, recent studies have explored AI’s ability to decode brain activity and reconstruct the images seen by individuals, the sounds heard, or even the stories imagined, by generating comparable images, streams of text, and even tunes. — Read More
Daily Archives: September 21, 2023
OpenAI releases third version of DALL-E
OpenAI announced the third version of its generative AI visual art platform DALL-E, which now lets users use ChatGPT to create prompts and includes more safety options.
DALL-E converts text prompts to images. But even DALL-E 2 got things wrong, often ignoring specific wording. The latest version, OpenAI researchers said, understands context much better.
A new feature of DALL-E 3 is integration with ChatGPT. By using ChatGPT, someone doesn’t have to come up with their own detailed prompt to guide DALL-E 3; they can just ask ChatGPT to come up with a prompt, and the chatbot will write out a paragraph (DALL-E works better with longer sentences) for DALL-E 3 to follow. Other users can still use their own prompts if they have specific ideas for DALL-E. — Read More
Contrastive Decoding Improves Reasoning in Large Language Models
We demonstrate that Contrastive Decoding — a simple, computationally light, and training-free text generation method proposed by Li et al 2022 — achieves large out-of-the-box improvements over greedy decoding on a variety of reasoning tasks. Originally shown to improve the perceived quality of long-form text generation, Contrastive Decoding searches for strings that maximize a weighted difference in likelihood between strong and weak models. We show that Contrastive Decoding leads LLaMA-65B to outperform LLaMA 2, GPT-3.5 and PaLM 2-L on the HellaSwag commonsense reasoning benchmark, and to outperform LLaMA 2, GPT-3.5 and PaLM-540B on the GSM8K math word reasoning benchmark, in addition to improvements on a collection of other tasks. Analysis suggests that Contrastive Decoding improves over existing methods by preventing some abstract reasoning errors, as well as by avoiding simpler modes such as copying sections of the input during chain-of-thought. Overall, Contrastive Decoding outperforms nucleus sampling for long-form generation and greedy decoding for reasoning tasks, making it a powerful general purpose method for generating text from language models. — Read More
ChatGPT diagnoses ER patients ‘like human doctor’
Artificial intelligence chatbot ChatGPT diagnosed patients rushed to emergency at least as well as doctors and in some cases outperformed them, Dutch researchers have found, saying AI could “revolutionize the medical field.”
But the report published on Sept. 13 also stressed ER doctors needn’t hang up their scrubs just yet, with the chatbot potentially able to speed up diagnosis but not replace human medical judgement and experience. — Read More
GPT 3.5 vs Llama 2 fine-tuning: A Comprehensive Comparison
In this post, I document my experiments benchmarking the fine-tuning of GPT 3.5 against Llama 2 in an SQL task and a functional representation task. Overall:
- GPT 3.5 performs marginally better against a Lora fine-tuned CodeLlama 34B (the model I found to work the best) on both datasets
- GPT 3.5 costs 4-6x more to train (and even more to deploy)
Code and data for SQL task is here. Code and data for functional representation task is here. — Read More
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