Infinity, Inc.’s Post

Ever wondered how leading language models like #LLMs evaluate the outputs of their counterparts in a way that's strikingly humanlike? Check out this blog to uncover the intricacies behind machine 'self-assessment' and why it's revolutionizing the way we think about AI interactions👇

Ever wondered how leading language models like #LLMs evaluate the outputs of their counterparts in a way that's strikingly humanlike? Check out this blog to uncover the intricacies behind machine 'self-assessment' and why it's revolutionizing the way we think about AI interactions👇

Ever wondered how leading language models like #LLMs evaluate the outputs of their counterparts in a way that's strikingly humanlike? Check out this blog to uncover the intricacies behind machine 'self-assessment' and why it's revolutionizing the way we think about AI interactions👇

Ever wondered how leading language models like #LLMs evaluate the outputs of their counterparts in a way that's strikingly humanlike? Check out this blog to uncover the intricacies behind machine 'self-assessment' and why it's revolutionizing the way we think about AI interactions👇

Ever wondered how leading language models like #LLMs evaluate the outputs of their counterparts in a way that's strikingly humanlike? Check out this blog to uncover the intricacies behind machine 'self-assessment' and why it's revolutionizing the way we think about AI interactions👇

Did you miss Episode 1 of our Graph Hunter Webinar series, "The Genesis Idea"? No problem! Watch the recording to explore the fascinating concepts we discussed. Explore the power of Argos and its mission to revolutionize investigations. Learn how Large Language Models and ArangoDB merge to amplify capabilities and turn data into action. Uncover the reasons behind merging AI with knowledge graphs and witness the transformation of operational efficiency. Don't miss out! Watch today and be part of the revelation shaping data-driven investigations. 🚀 https://okt.to/HtTVQk #ArgosWebinar #DataRevolution #WatchNow

"Despite the appearance of science, most developers really judge models based on vibes or instinct" This quote comes from the New York Time's article today: AI Has a Measurement Problem. I've been working with many enterprises since Chat GPT blew up and "vibes or instinct" doesn't quite cut it when an organization is investing millions into a generative AI project that they are EXPECTING to deliver a business outcome. And this is exactly why I came to 🔭 Galileo NYT article in the comments along with a link to the research paper discussing our novel approach for LLM performance - beating industry standards aka the next best theoretical algorithm by 11% 😎

Harness the simplicity of a natural language interface to effortlessly connect you to your organization’s wealth of information and assets! With the ability to answer questions in multiple languages, transcribe speech to text, and trace its information sources, our Generative AI Knowledge Base is your key to seamless knowledge access! Build your knowledge base today: https://bit.ly/3RImozn #BuildOnBedrock

With bias aside, any customer or prospect should allow Caylent a seat at the table for any GenAI conversation. We are actively helping our customers adopt AI responsibly while leveraging disruptive technology that is accelerating their growth. #Disruption #GenAI #AWS #Bedrock

The more we engage with AI, the more opaque our comprehension of these interactions becomes. This irony presents a contemporary take on the longstanding "black box" dilemma: The “black box” problem refers to the opaque decision-making processes of ML models (large language models (LLMs) including), where the rationale behind any given response is shrouded in complexity. Despite advances in technology, the inner workings of these models, governed by billions or soon trillions of parameters, remain largely inscrutable. Their decision-making is a puzzle, complicated by nonlinear interactions that defy straightforward interpretation. Prompting doesn’t make it any better: we now have obscured layers of communication activated with every prompt. What we see — the prompt we type — is merely the surface. So, if you were confused about prompting amid the avalanche of articles, blogs, and tutorials about it — you should be. Write what I've found about it and join the discussion: https://lnkd.in/erJGSAUf