Adriel De vera

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on the atlas · 19

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The World Economic Forum reports that workers typically hold an average of 12 different jobs throughout their lifetime, with Gen Z expected to hold 18 jobs across 6 different careers.
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An AI model capable of making inferences can do so without examples of the desired result. In other words, inference is an AI model in action.
AI inference vs. training: What is AI inference? | Cloudflare
• Front End Agent (gpt-3.5-turbo based): Generates responses with potential hallucinations. • Second Level Reviewer (gpt-4o based): Refines the Front End Agent’s response, reducing hallucinations and adding disclaimers, and inserts its responses in an OVON JSON message. • Third Level Reviewer (gpt-4o based): Further refines the Second Level Reviewer’s response, minimizing hallucinations and strengthening disclaimers.
Hallucination Mitigation using Agentic AI Natural Language-Based Frameworks
Anyone in 2035 should be able to marshall the intellectual capacity equivalent to everyone in 2025; everyone should have access to unlimited genius to direct however they can imagine
Three Observations - Sam Altman
OpenAI said it tested ChatGPT deep research using Humanity’s Last Exam, an evaluation that includes more than 3,000 expert-level questions in a variety of academic fields. The o3 model powering deep research achieved an accuracy of 26.6%, which might look like a failing grade — but Humanity’s Last Exam was designed to be tougher than other benchmarks to stay ahead of model advancements. According to OpenAI, the deep research o3 model came in way ahead of Gemini Thinking (6.2%), Grok-2 (3.8%), and OpenAI’s own GPT-4o (3.3%).
OpenAI unveils a new ChatGPT agent for ‘deep research’ | TechCrunch
3) the potential for further global expansion for Chinese players, given their performance and cost/price competitiveness.
DeepSeek 'punctures' AI leaders' spending plans, and what analysts are saying | TechCrunch
2) from training to more inferencing, with increased emphasis on post-training (including reasoning capabilities and reinforcement capabilities) that requires significantly lower computational resources vs. pre-training;
DeepSeek 'punctures' AI leaders' spending plans, and what analysts are saying | TechCrunch
1) potential competition between capital-rich internet giants vs. start-ups, given lowering barriers to entry,
DeepSeek 'punctures' AI leaders' spending plans, and what analysts are saying | TechCrunch
Perplexity has increasingly invested in corporate-focused functionality, last summer launching an enterprise plan with user management, “internal knowledge search,” and more.
Perplexity acquires Read.cv, a social media platform for professionals | TechCrunch
In the above example, you could just make a multi-step agent that has access to a weather API for weather forecasts, Google Maps API to compute travel distance, an employee availability dashboard and a RAG system on your knowledge base.
smolagents
I can come on Monday, but I forgot my passport so risk being delayed to Wednesday, is it possible to take me and my stuff to surf on Tuesday morning, with a cancellation insurance?"
smolagents
The question is: do I really need flexibility in the workflow to efficiently solve the task at hand
smolagents
By eliminating the need for real-time retrieval, CAG significantly reduces inference latency, enabling faster responses to user queries.
CAG: Improve RAG Framework using Cache | by Mehul Gupta | Data Science in your pocket | Jan, 2025 | Medium
CAG removes the need for integrating retrieval and generation components, reducing system complexity and maintenance overhead.
CAG: Improve RAG Framework using Cache | by Mehul Gupta | Data Science in your pocket | Jan, 2025 | Medium