Listen "Mistral New Models 🗣️ // Mistral-Microsoft Partnership 💻 // Input Length Impact on LLMs 🤔"
Episode Synopsis
Mistral AI has launched a new conversational assistant, Le Chat Mistral, which serves as an entry point to interact with their various models. They're also launching Le Chat Enterprise, which could be useful for businesses looking to boost productivity and efficiency.
Microsoft has partnered with Mistral, a French company focused on language models, and will be taking a minor stake in the company and offering their language models on Azure AI platform. Mistral is also releasing a new model called Mistral Large, which is designed to compete with OpenAI's GPT-4 model.
"Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models" by Levy et al. investigates how the performance of Large Language Models (LLMs) changes when the input length is extended. The authors found that there is a notable degradation in LLMs' reasoning performance at much shorter input lengths than their technical maximum.
"Executable Code Actions Elicit Better LLM Agents" proposes using executable Python code to consolidate LLM agents' actions into a unified action space called CodeAct. CodeAct outperforms widely used alternatives by up to 20% higher success rate and could have a lot of practical applications.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:39 Le Chat announced by Mistral AI
02:53 Microsoft partners with Mistral in second AI deal beyond OpenAI
04:29 Introducing Phind 70Billion
05:27 Fake sponsor
07:05 Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
08:47 Executable Code Actions Elicit Better LLM Agents
10:36 Cleaner Pretraining Corpus Curation with Neural Web Scraping
12:20 Outro
Microsoft has partnered with Mistral, a French company focused on language models, and will be taking a minor stake in the company and offering their language models on Azure AI platform. Mistral is also releasing a new model called Mistral Large, which is designed to compete with OpenAI's GPT-4 model.
"Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models" by Levy et al. investigates how the performance of Large Language Models (LLMs) changes when the input length is extended. The authors found that there is a notable degradation in LLMs' reasoning performance at much shorter input lengths than their technical maximum.
"Executable Code Actions Elicit Better LLM Agents" proposes using executable Python code to consolidate LLM agents' actions into a unified action space called CodeAct. CodeAct outperforms widely used alternatives by up to 20% higher success rate and could have a lot of practical applications.
Contact: [email protected]
Timestamps:
00:34 Introduction
01:39 Le Chat announced by Mistral AI
02:53 Microsoft partners with Mistral in second AI deal beyond OpenAI
04:29 Introducing Phind 70Billion
05:27 Fake sponsor
07:05 Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
08:47 Executable Code Actions Elicit Better LLM Agents
10:36 Cleaner Pretraining Corpus Curation with Neural Web Scraping
12:20 Outro
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