Imperial AI initiative I-X to collaborate with @Fetch_ai on ‘new AI economy'https://www.imperial.ac.uk/news/249754/imperial-ai-initiative-i-x-collaborate-with/ #AI #AGI #LLM #AgentEd
Imperial AI initiative I-X to collaborate with Fetch.ai on ‘new AI economy' | Imperial News | Imperial College London

AI startup Fetch.ai has joined I-X Business Partners, the corporate membership programme of Imperial’s flagship initiative in artificial intelligence.

Imperial News
How Autonomous AI Agents are Reshaping Industries and Redefining Expertise — Xyonix, AI Consulting & Custom Solutions

Recent advancements in AI technology have reshaped everyday life and industries, introducing autonomous functionality in products like Tesla's Autopilot and Roomba, and opening up new frontiers in complex problem-solving. This article explores the rapid progression towards a future where AI is not j

Xyonix, AI Consulting & Custom Solutions
Autonomous Driving (AD) goes hand in hand with Autonomous Agents (AA) 👉 https://arxiv.org/pdf/1911.04175.pdf #FetchAI #AutonomousAgents #AgentEd #Datarella #moveID
What was still being discussed in scientific papers in 2016 is a reality today https://arxiv.org/pdf/1610.03295.pdf
Can’t wait to bring @Fetch_ai Autonomous Agents to the street! With @moveID_gaiax and @MOBIXWALLET
#AutonomousAgents #FetchAI #Datarella #AgentEd #AI
Get Ready for ChatGPT-Style AI Chatbots That Do Your Boring Chores

Move over, Siri. Startups are using the technology behind ChatGPT to build more capable AI agents that can control your computer and access the web to get things done—with sometimes chaotic results.

WIRED
How ‘A.I. Agents’ That Roam the Internet Could One Day Replace Workers

Researchers are transforming chatbots into online agents that play games, query websites, schedule meetings, build bar charts and do more.

The New York Times
Will AI Use Crypto? Here’s What’s Driving AI Token FOMO

Will crypto be the currency of choice for the AI of the future? Crypto investors are betting on it.

Decrypt
Revolutionizing Autonomous Agents: AGENTS Framework Puts Power in Your Hands | Synced

In recent years, the rapid progress of Large Language Models (LLMs) has showcased their potential in creating autonomous agents capable of tackling complex tasks and engaging with the world, humans, and fellow agents through a profound understanding of their surroundings. However, despite this promising trajectory, the creation of such agents remains a significant challenge for

Synced | AI Technology & Industry Review
Sparks of Artificial General Intelligence: Early experiments with GPT-4 https://arxiv.org/abs/2303.12712 #AutonomousAgents #AI #AgentEd #Datarella
Sparks of Artificial General Intelligence: Early experiments with GPT-4

Artificial intelligence (AI) researchers have been developing and refining large language models (LLMs) that exhibit remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. The latest model developed by OpenAI, GPT-4, was trained using an unprecedented scale of compute and data. In this paper, we report on our investigation of an early version of GPT-4, when it was still in active development by OpenAI. We contend that (this early version of) GPT-4 is part of a new cohort of LLMs (along with ChatGPT and Google's PaLM for example) that exhibit more general intelligence than previous AI models. We discuss the rising capabilities and implications of these models. We demonstrate that, beyond its mastery of language, GPT-4 can solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting. Moreover, in all of these tasks, GPT-4's performance is strikingly close to human-level performance, and often vastly surpasses prior models such as ChatGPT. Given the breadth and depth of GPT-4's capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. In our exploration of GPT-4, we put special emphasis on discovering its limitations, and we discuss the challenges ahead for advancing towards deeper and more comprehensive versions of AGI, including the possible need for pursuing a new paradigm that moves beyond next-word prediction. We conclude with reflections on societal influences of the recent technological leap and future research directions.

arXiv.org