Agent Q 🧩, Former Google CEO Eric Schmidt’s Vision of AI’s Future 🌐 , Salesforce’s xGen-MM 📂

NVIDIA Webinar, September 10-11, Build Visual AI Agents With Generative AI and NVIDIA NIM, Register Now

September 18-19, 2024 The AI Conference 2024 | San Francisco, USA Register Now

Introducing Agent Q: Next Generation of AI Agents with Planning & Self Healing Capabilities

Agent Q is an advanced AI system developed by AGI in collaboration with Stanford University, designed to tackle complex, multi-step decision-making tasks in dynamic environments. Unlike traditional AI models, which excel at static tasks, Agent Q integrates Monte Carlo Tree Search (MCTS) and Direct Preference Optimization (DPO) to navigate and adapt to unpredictable scenarios. These techniques enable Agent Q to explore various actions, learn from both successes and failures, and improve its decision-making abilities over time.

Key Features of Agent Q

Guided Search with Monte Carlo Tree Search (MCTS)
MCTS allows Agent Q to explore various actions and determine the best outcomes by balancing exploration and exploitation.

AI Self-Critique Mechanism
Agent Q self-evaluates its decisions at each step, learning from both successes and mistakes to improve over time.

Direct Preference Optimization (DPO)
DPO enables Agent Q to learn from the entire decision-making process by constructing preference pairs, rather than just binary outcomes.

Autonomous, Self-Healing, and Multi-Tasking Capabilities
Agent Q autonomously navigates web environments, self-corrects when issues arise, and efficiently handles multiple tasks simultaneously.

Real-World Applications and Challenges

In real-world applications, Agent Q has demonstrated superior performance, significantly outperforming traditional models in tasks like restaurant reservations on OpenTable. However, challenges remain, such as incorporating more human oversight and refining search algorithms. Agent Q's ability to learn and adapt in real-time points to a future where AI systems are defined by intelligent exploration rather than vast amounts of data.

Agent Q is poised to set a new standard for autonomous AI agents, capable of efficiently and accurately handling tasks in real-world scenarios.

Read the full version Here!

Former Google CEO “Eric Schmidt” Reveal The Dark Secrets Behind Winning the AI Race

Eric Schmidt, former CEO of Google, recently delivered a controversial talk at Stanford University, where he made bold predictions about the future of AI and sharply criticized Google's current corporate culture. Schmidt foresees AI having an incomprehensible impact on society, even greater than that of social media. He emphasized advancements like expanding context windows and autonomous AI agents that continuously learn and improve, predicting that AI will revolutionize industries in unimaginable ways.

Schmidt also criticized Google for prioritizing work-life balance over competitiveness, suggesting that this focus may be causing the company to lose its edge, especially as startups push forward with relentless work ethics. He controversially advised AI startups that it's acceptable to "steal content" if they can succeed, citing Google's own early legal maneuvering as an example.

Schmidt highlighted Nvidia's dominance in AI hardware due to its early investment in GPU technology and warned of the geopolitical AI race between the U.S. and China, emphasizing the high stakes involved. His talk sparked debate over the balance between relentless pursuit of AI advancements and maintaining ethical considerations and work-life balance.

Schmidt's vision serves as both a roadmap and a warning for the future of AI, urging tech giants to navigate the evolving landscape without losing sight of their core values, while suggesting that only those willing to work tirelessly will succeed in the AI-driven world.

Read the full version Here!

Salesforce releases 'xGen-MM' open-source multimodal AI models

Salesforce AI Research has introduced a new series of open-source large multimodal models (LMMs) called xGen-MM, also known as BLIP-3. These models represent a significant advancement in AI's ability to understand and generate content that combines text, images, and other data types. The xGen-MM models are trained on massive datasets, including a trillion-token scale interleaved image-text dataset called MINT-1T. They are designed to handle complex tasks like answering questions about multiple images simultaneously, with variants optimized for different purposes, including instruction-following and safety-tuning.

Salesforce's decision to open-source these models, along with the datasets and fine-tuning code, is aimed at democratizing access to advanced AI technology and accelerating innovation in the field. This move contrasts with the more closed approaches of other tech giants and could foster a more collaborative ecosystem around multimodal AI research.

However, the release of such powerful models raises concerns about potential risks and societal impacts, despite the safety measures included. Salesforce's open approach may set a new standard for transparency in AI development and could pressure other companies to follow suit. The xGen-MM models and resources are available on Salesforce’s GitHub repository, with further resources to be released soon. The long-term impact of this release on the AI landscape will unfold as researchers and developers begin to work with these tools.

Build your own AI-powered robot: Hugging Face’s LeRobot tutorial is a game-changer
Hugging Face has released a comprehensive tutorial for building AI-powered robots, significantly lowering the entry barrier for developers. This initiative democratizes robotics, traditionally dominated by large corporations, by providing step-by-step guidance on sourcing parts, assembling, and deploying AI models. The tutorial, featuring the Koch v1.1 robotic arm, emphasizes practical applications and community collaboration, enabling developers to share data and advance AI-driven robotics.

Google's AI search gives websites dire choice: Share data or die
Publishers are facing a tough choice with Google's AI search feature: allow their content to be used in AI-generated summaries at the top of search results, risking reduced traffic to their sites, or block Google's AI bot, which could result in their websites being less discoverable in Google searches. This situation is creating an "existential crisis" for many content creators, as they struggle to balance visibility with protecting their content. Google's dominance in search exacerbates the issue, limiting publishers' leverage in negotiations.

Alibaba and Tencent clouds see demand for CPUs level off, GPUs accelerate
Tencent, Alibaba, and Lenovo reported mixed financial results, reflecting broader challenges in China's tech sector. Tencent's revenue grew by 11%, driven by its online gaming and fintech divisions, but Alibaba faced slower growth due to weaker consumer demand. Lenovo, meanwhile, saw a decline in revenue and profit, attributed to the global downturn in the PC market. The companies are navigating a challenging economic environment, with varying degrees of success in adapting to market conditions.


Former Huawei ‘Genius Youth’ recruit launches humanoid robots to rival Tesla’s Optimus
Elon Musk's AI startup, xAI, has introduced a tool that allows users to generate AI images directly on Twitter (now X), sparking outrage due to concerns over the potential for misuse. Critics fear this could exacerbate the spread of misinformation and deepfakes, raising ethical and security issues as powerful AI tools become more integrated into social media platforms. This controversy underscores the broader anxieties about AI's impact on public discourse.

Microsoft is Offering FREE Courses For Everyone No Fee, No Subscription No Registration Required, Apply Now

👥 Connect & Feedback!

👉 Join Us:

📧 Advertise In Weekly AI News:

📧 Contact directly at [email protected]

😍 Share with your friends!