So many people are confused about the relation between human cognitive errors and LLM hallucinations that I wrote this short explainer: Humans say things that aren't true for many different reasons
• Sometimes they lie
• Sometimes they misremember things
• Sometimes they fail
GENERATIVE AI
-
Human Cognitive Errors vs LLM Hallucinations Explained
By
–
-
Replicate and Infomaniak for hosting LLMs
By
–
Replicate is all you need. Otherwise check out @infomaniak to host LLMs, they have cool stuff.
-
Groq Predicts Exciting Second Half of 2024 with Growth
By
–
The rest of 2024 is going to be a lot of fun as we keep building out more capacity, we see open source providing more models, and the dev community is hitting it's creative stride making amazing apps. We're not even halfway into the year and it's ⚡️⚡️⚡️ right now! https://t.co/UlXXTpGTzr pic.twitter.com/wYU6dr8IaF
— Groq Inc (@GroqInc) 21 avril 2024The rest of 2024 is going to be a lot of fun as we keep building out more capacity, we see open source providing more models, and the dev community is hitting it's creative stride making amazing apps. We're not even halfway into the year and it's right now!
-
Multimodal World Models: The Future of Grounded AI Systems
By
–
How to attain Multimodal World Models is a great open question in AI. The solutions will likely lead to more grounded models that interact better with people and make better physics predictions. Hopefully, they will enable scientific generalisation, but this too I feel is an open
-
5 Types of Generative AI Redefining Creativity and Innovation
By
–
From style transfer to text generation, #GenerativeAI is redefining creativity and innovation. Delve into these 5 types and see AI's potential unfold. Follow @ingliguori for a journey into the future of #AI, and discover 'The Digital Edge' to stay ahead! https://
bit.ly/3u4pILl -
Emerging AI Agent Architectures: Reasoning, Planning, and Tool Calling
By
–
8/ Emerging AI Agent Architectures – a summary of emerging AI agent architectures; it focuses the discussion on capabilities like reasoning, planning, and tool calling which are all needed to build complex AI-powered agentic workflows and systems.
-
RAG Reduces Hallucination in LLM Structured Outputs
By
–
7/ Reducing Hallucination in Structured Outputs via RAG – shows that RAG can enable deploying powerful LLM-powered systems in limited-resource settings while mitigating issues like hallucination and increasing the reliability of outputs.
-
Top ML Papers Week: Llama 3, Mixtral, RAG Advances
By
–
The Top ML Papers of the Week (April 15 – April 21): – Llama 3
– Mixtral 8x22B
– A Survey on RAG
– How Faithful are RAG Models?
– Emerging AI Agent Architectures
– Chinchilla Scaling: A replication attempt
… -
Llama 3 Family: 8B and 70B Models Released with Strong Performance
By
–
1/ Llama 3 – a family of LLMs that include 8B and 70B pretrained and instruction-tuned models; Llama 3 8B outperforms Gemma 7B and Mistral 7B Instruct; Llama 3 70 broadly outperforms Gemini Pro 1.5 and Claude 3 Sonnet.https://t.co/xqDJy0f0Vs
— DAIR.AI (@dair_ai) 21 avril 20241/ Llama 3 – a family of LLMs that include 8B and 70B pretrained and instruction-tuned models; Llama 3 8B outperforms Gemma 7B and Mistral 7B Instruct; Llama 3 70 broadly outperforms Gemini Pro 1.5 and Claude 3 Sonnet.
-
Anticipating Code Interpreter Feature on Claude 3
By
–
Really looking forward to Code Interpreter on Claude 3