If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Evaluate conversational LLM apps like ChatGPT in 3 steps (open-source).Unlike single-turn tasks, conversations unfold over multiple messages.This means that the LLM's behavior must be consistent, compliant, and context-aware across turns, not just accurate in one-shot output. https://t.co/dugCyqQl6D ...

To kick off, @Kaggle is hosting a 3-day exhibition chess tournament with matches between some of the top LLMs - w/commentary from chess legends @MagnusCarlsen, @GMHikaru, @GothamChess. Tune in at 10:30am PT starting tmrw (Aug 5th), should be a lot of fun: https://t.co/PNTk1vLlp2 ...

Thrilled to announce the @Kaggle Game Arena, a new leaderboard testing how modern LLMs perform on games (spoiler: not very well atm!). AI systems play each other, making it an objective & evergreen benchmark that will scale in difficulty as they improve.https://t.co/0e2dF2pbtX ...

Product Features - CoinGecko MCP enables LLMs to access real-time market data, including token prices, market capitalization, and trading volume [1] - The guide details the features of CoinGecko's MCP, setup instructions, and use cases for enhancing crypto research [1]

[Music] I'm going to be giving a quick presentation about the state of the union regarding AI vision. Um, so I'm Peter Robisho. I'm the ML lead at Rooflow, which is a platform for building and deploying vision models.Um, so a lot of people are really interested in LLMs these days. So I'm trying to pitch why computer vision matters. Uh so if you think about systems that interact with the real world, they have to use vision as one of their primary inputs because the the built world is sort of built around vis ...

The US government spends hundreds of billions of dollars a year on consulting. As you might imagine, this isn't the most efficient or innovative part of our economy. But the last couple years, we believe that there are a few big reasons that this will change.Most importantly, today there is political pressure to cut wasteful consulting and spending. Every part of the government now runs on software. This software is usually customuilt by companies like Deote or Accenture.And anyone who used the software kno ...

Core Viewpoint - Alphabet's defeat in antitrust court and the perceived threat from large language models (LLMs) to its search engine advertising revenue contribute to a narrative of an existential crisis for the company [1] Group 1: Antitrust Issues - Alphabet has faced a significant defeat in antitrust court, which raises concerns about its market position and regulatory challenges [1] Group 2: Impact of LLMs - The rise of LLMs is viewed as potentially positive for the industry, suggesting that these technologies could enhance overall market dynamics rather than pose a direct threat to Alphabet [1]

AI Engineering Landscape - The AI engineering community is broad, technical, and growing, with the "AI Engineer" title expected to gain more ground [5] - Many seasoned software developers are AI newcomers, with nearly half of those with 10+ years of experience having worked with AI for three years or less [7] LLM Usage and Customization - Over half of respondents are using LLMs for both internal and external use cases, with OpenAI models dominating external, customer-facing applications [8] - LLM users are leveraging them across multiple use cases, with 94% using them for at least two and 82% for at least three [9] - Retrieval-Augmented Generation (RAG) is the most popular customization method, with 70% of respondents using it [10] - Parameter-efficient fine-tuning methods like LoRA/Q-LoRA are strongly preferred, mentioned by 40% of fine-tuners [12] Model and Prompt Management - Over 50% of respondents are updating their models at least monthly, with 17% doing so weekly [14] - 70% of respondents are updating prompts at least monthly, and 10% are doing so daily [14] - A significant 31% of respondents lack any system for managing their prompts [15] Multimodal AI and Agents - Image, video, and audio usage lag text usage significantly, indicating a "multimodal production gap" [16][17] - Audio has the highest intent to adopt among those not currently using it, with 37% planning to eventually adopt audio [18] - While 80% of respondents say LLMs are working well, less than 20% say the same about agents [20] Monitoring and Evaluation - Most respondents use multiple methods to monitor their AI systems, with 60% using standard observability and over 50% relying on offline evaluation [22] - Human review remains the most popular method for evaluating model and system accuracy and quality [23] - 65% of respondents are using a dedicated vector database [24] Industry Outlook - The mean guess for the percentage of the US Gen Z population that will have AI girlfriends/boyfriends is 26% [27] - Evaluation is the number one most painful thing about AI engineering today [28]

Hackathon Overview - CoinGecko is hosting an MCP Hackathon focused on building with crypto price data and AI [1] - The hackathon encourages participation from builders, researchers, and tinkerers [1] Prizes and Incentives - The hackathon offers prizes worth up to $13,000 [1] - Over $1,300 in prizes are specifically allocated for projects utilizing CoinGecko's crypto price data in AI and LLMs [1] Participation Details - Participants are invited to BuildwithCoinGecko and AI [1] - Interested individuals can find participation details at the provided URL [1]

Key Features - MCP-use 简化了 LLMs 连接到 MCP 服务器和构建本地 MCP 客户端的过程 [1] - 该工具与 Ollama 和 LangChain 兼容 [2] - 支持异步流式传输 Agent 的输出 [2] - 内置调试模式 [2] - 可以限制 MCP 工具的使用 [2]