The #GenerativeAI DataLLM from @abacusai uses #LLMs to generate insights from all your data sources! You pose questions about your data to the #chatbot — the #AI agent then generates code, runs queries, understands results, & presents answers. See
LLMS
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Specialized Models Outperform General-Purpose LLMs for Enterprise
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Myth: General-purpose #LLMs can solve all enterprise business challenges.
— AI21 Labs (@AI21Labs) 19 février 2024
Fact: Smaller, specialized models, deliver superior results.
Learn more about our Task-Specific models. 👇 https://t.co/hUgtGPShRz pic.twitter.com/X7oOUzba8mMyth: General-purpose #LLMs can solve all enterprise business challenges. Fact: Smaller, specialized models, deliver superior results. Learn more about our Task-Specific models. https://
ai21.com/meeting/contact -
Yann LeCun shares AI knowledge burden with Llama3
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@ylecun
, ever feel like you're cursed with knowledge, akin to Iron Man? No worries if the world's indifferent—perhaps sharing a secret or two with Llama3 might lighten the burden. How about it? -
Mistral releases new AI model ‘next’ rivaling GPT-4
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French AI startup Mistral quietly released a new model called ‘next’ in testing. Early users are reporting capabilities meet or surpass GPT-4 in early evaluations. The stealth drop could be a milestone moment for open source if early tests hold up.
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LLMCompiler: Fast Parallel Agent Task Execution with LangGraph
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LLMCompiler: blazing-fast agent execution Plan tasks as a DAG.
Stream parallelized task execution (while the planner is still thinking!)
Respond or replan. Build it for yourself in LangGraph! Python: https://
github.com/langchain-ai/l
anggraph/blob/main/examples/llm-compiler/LLMCompiler.ipynb
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Youtube: https://
youtu.be/uRya4zRrRx4?fe
ature=shared&t=1183
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Conversational AI Development: Three Key Challenges Solutions
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3 Crucial Challenges in Conversational AI Development and How to Avoid Them: Developing a conversational AI chatbot requires substantial effort. However, understanding and addressing key challenges in natural language understanding can streamline the… https://
kdnuggets.com/3-crucial-chal
lenges-in-conversational-ai-development-and-how-to-avoid-them?utm_source=dlvr.it&utm_medium=twitter&utm_campaign=3-crucial-challenges-in-conversational-ai-development-and-how-to-avoid-them
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Neural Networks Without Symbolic Representations Vulnerable to Hallucinations
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Literally I have arguing for 23 years that neural nets without symbolic representations would be vulnerable to hallucinations, and they have. And literally every year (often daily) I have heard promissory notes like these, and never seen a detailed technical explanation as to https://
x.com/saehtweets/sta
/saehtweets/status/1759329436007112736
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LLMs Limitations: Statistical Prediction Over True Reasoning
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the solutions not come from within LLMs; they are doing the wrong kind of computation, which has nothing to do with facts and reasoning, and pertains only to prediction. The statistical inference has steadily improved with more data; problems with factuality and reliability
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Multimodal AI Features: Image and Video Input Roadmap
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Still dope! Hope image/video inputs are on the roadmap.
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OpenAI system messages: enabling upfront parameters for users
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Heyo @OfficialLoganK @OpenAI is there a way to start with a system message like Poe has? The conversation starters seem to be more for the user to answer, but I want users to provide upfront parameters without needing to think (ie the system just prompts with the ask).