RT BSCN (@BSCNews)🚨 2025 DEEP DIVE: $PORT3 - With more than 5 million users and a unique approach to AI agents, @Port3Network is one you need to know about...https://t.co/CYCa85ND3o ...

🚨 2025 DEEP DIVE: $PORT3 - With more than 5 million users and a unique approach to AI agents, @Port3Network is one you need to know about...https://t.co/CYCa85ND3o ...

Core Business & Services - Kalin builds custom solutions for clients, ranging from Fortune 500 companies to startups, focusing on app development and database migrations [1][2] - The company leverages generative AI to automate business functions, such as intelligent document processing for logistics management, achieving faster and better results than human annotators [20][21] - Kalin offers services ranging from chatbot and co-pilot development to AI agent creation, tailoring solutions to specific client needs [16] Technology & Architecture - The company utilizes multimodal search and semantic understanding of videos, employing models like Nova Pro and Titan v2 for indexing and searching video content [6][7] - Kalin uses various databases including Postgress, PG vector, and OpenSearch for vector search implementations [13] - The company builds AI systems on AWS, utilizing services like Bedrock and SageMaker, and custom silicon like Tranium and Inferentia for price performance improvements of approximately 60% over Nvidia GPUs [27] AI Development & Strategy - Prompt engineering has proven highly effective, sometimes negating the need for fine-tuning models [40] - Context management is crucial for differentiating applications, leveraging user data and history to make strategic inferences [33][34] - UX design is important for mitigating the slowness of inference, with techniques like caching and UI spinners improving user experience [36][37]

New Starboard is Live 🌠 @BlueprintAIxDive into how Blueprint is automating every onchain action using AI agents like Nest, your crypto wealth manager.Up to $50K worth of Blueprint’s upcoming token will go to top aura leaders. Build your aura: https://t.co/RsoWGfgADa https://t.co/7SXwBzJ3on ...

This startup thinks email could be the key to usable AI agents | TechCrunch https://t.co/wupAztf0Zs ...

Agent Capabilities & Architecture - OpenAI has created a new agent in ChatGPT that can perform tasks that would take humans a long time, by giving the agent access to a virtual computer [6] - The agent has access to a text browser (similar to deep research tool), a virtual browser (similar to operator tool with full GUI access), and a terminal for running code and calling APIs [6][7][8] - All tools have shared state, allowing for flexible and complex tasks [9] - The agent is trained using reinforcement learning across thousands of virtual machines, allowing it to discover optimal strategies for tool usage [3] Development & Training - The agent is a collaboration between the Deep Research and Operator teams, combining the strengths of both [6] - The agent is trained with reinforcement learning, rewarding efficient and correct task completion [36] - The model figures out when to use which tool through experimentation, without explicit instructions [38] - Reinforcement learning is data-efficient, allowing new capabilities to be taught with smaller, high-quality datasets [75][76] Safety & Limitations - Safety training and mitigations were a core part of the development process due to the agent's ability to take actions with external side effects [44] - The team has implemented a monitor that watches for suspicious activity, similar to antivirus software [48] - Date picking remains a difficult task for the AI system [4][83][84] Future Directions - Future development will focus on improving the accuracy and performance across a wide distribution of tasks [62][85] - The team is exploring different ways of interacting with the agent, beyond the current chat-based interface [68][86] - Personalization and memory for agents will be important for future development, allowing agents to do things without being explicitly asked [67][68]

RT Bloomberg Live (@BloombergLive).@IBM's Greg Pollack will kickoff #ValueOfAI with insights into how AI agents can improve the customer experience and transform how work gets done. Join us in Atlanta on 8/12: https://t.co/gTcAtkN1C3 https://t.co/KkFi6oTetU ...

Why a Y Combinator startup tackling AI agents for Windows gave up and pivoted | TechCrunch https://t.co/inNH6P88kJ ...

Agentic Economy & MCP Standard - The agentic economy is emerging, where AI agents can interact, find counterparts, and purchase services from other agents, businesses, or tools [4] - MCP (Message Communication Protocol) is becoming a standard for agentic interaction, dominating the space compared to Open API and Google's A2A [8][9] - Tool discovery, a key feature of MCP, allows agents to dynamically discover and use tools based on the workflow, differentiating it from Open API [7][8] - A centralized marketplace of MCP services, like APIFY, can provide access to various services with a single API token, enabling rapid scaling of the ecosystem [12] APIFY's Role & Marketplace - APIFY is a marketplace of 5,000 tools (actors), primarily data extraction tools, with a community of creators who monetize their tools [4] - Actors are self-contained software units with defined input and output, facilitating easy integration with other systems [4][5] - APIFY has integrations with workflow automation tools and MCP, enabling AI agents to call actors from the marketplace [6][7] - APIFY enables publishing and monetization of tools or agents, providing access to a broad ecosystem of developers and visibility [23][24] Challenges & Future - Agents currently rely on human developers for access to tools and services, hindering their ability to autonomously find and purchase services [10][11] - Trust between agents and tools is a key open question, as is the overall value and reliability of autonomous tool discovery [25][26][27] - The company paid out over $4 million to creators last month, with actors generating over $500,000 per month, indicating rapid ecosystem growth [23]

Core Insights - OpenAI is experiencing rapid growth and significant user engagement, yet it remains unprofitable, drawing parallels to Tesla's early years [1][2][3] - The company reported an 82% increase in annualized revenue, reaching $10 billion in the first half of 2025, but profitability is still not in sight [3][6] - OpenAI has over 800 million users and a valuation exceeding $300 billion, making it the third most valuable private company globally [4][6] Revenue and User Base - Consumer subscriptions contribute to 75% of OpenAI's revenue, highlighting the importance of its user base [4] - The total addressable market (TAM) for OpenAI could surpass $700 billion by 2030, indicating substantial growth potential [5] Competitive Landscape - OpenAI is focusing on AI agents that operate autonomously, aiming to challenge established hardware and ad-tech companies [6] - The competitive environment is intensifying with rivals like Google's Gemini and DeepSeek-R1, which could impact OpenAI's market position [5][6] Financial Outlook - Despite raising $63 billion for infrastructure and talent, OpenAI is not expected to achieve profitability until 2029, with a valuation at 27 times the estimated revenue for 2025 [6][7]