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Today:

• Former Insiders Reveal AI Dangers

• AI Writes 25% of Google's Code

• OpenAI Launches SimpleQA

• AWS Launches Rival to Copilot

• LinkedIn Introduces AI Hiring Assistant

• Google’s Gemini to Power Waymo Robotaxis

• AI Drives Google’s Q3 Success

Ex-OpenAI Employees Just EXPOSED The Truth About AGI....

In a Senate hearing, former AI company insiders stressed the urgent need for whistleblower protections in the tech industry. William Saunders, who left OpenAI, revealed that departing employees were pressured to sign non-disparagement agreements, forfeiting their equity if they refused. 

This practice silences employees who might report unethical behavior or risks posed by AI technologies. Due to a lack of regulations, many concerning actions aren't illegal, rendering existing whistleblower laws ineffective.

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AI Writes 25% of Google's Code

Google CEO Sundar Pichai announced that over 25% of new code at Google is now written by artificial intelligence (AI). This means that computers are helping to write more than a quarter of the company's new software. During Google's third-quarter earnings call, Pichai emphasized that AI is boosting productivity and efficiency within the company. 

While some critics believe tech giants overstate AI's benefits, Google claims it is making real progress by using AI to improve work processes and save resources. Pichai suggests this is just the beginning, indicating that AI will play an even larger role in the future.

OpenAI Launches SimpleQA

OpenAI has launched SimpleQA, a new test to check how accurately AI models can answer short, factual questions. The aim is to reduce "hallucinations," which are instances where AI provides incorrect or unfounded answers. SimpleQA uses clear questions with single, undeniable answers across a range of topics, making it challenging even for advanced AI models. 

The test helps compare different AI systems and assesses if they recognize when they don't know an answer. By having AI state its confidence level, researchers can see if the model's certainty matches its actual accuracy. OpenAI hopes SimpleQA will make AI more reliable and trustworthy.

AWS Launches Rival to Copilot

Amazon Web Services (AWS) has launched Amazon Q Developer, an in-line AI coding assistant, as a competitor to Microsoft’s GitHub Copilot. Available within popular coding environments like Visual Studio Code and JetBrains, Q Developer allows developers to highlight code for actions like “Optimize,” “Add comments,” and “Write tests.” Powered by Anthropic’s Claude 3.5 Sonnet, Q Developer aims to streamline coding tasks by integrating suggestions directly within the editor, saving developers from switching between chat and code windows. 

This tool offers a free tier with usage limits, while a Pro version costs $19/month. Amazon’s move underscores the competitive landscape, as both AWS and Microsoft aim to lead in AI-driven developer productivity.

LinkedIn Introduces AI Hiring Assistant

LinkedIn is upgrading its recruiting platform with a new feature called Hiring Assistant, which uses artificial intelligence (AI) to connect recruiters with potential job candidates. The AI reads job descriptions or prompts from recruiters and suggests candidates based on specific criteria. 

This helps recruiters focus on finding the right people instead of spending time on tasks like writing emails or copying job descriptions. The AI agents remember previous interactions and adjust their searches based on feedback, improving over time. LinkedIn's goal is to make AI a helpful tool that enhances recruiters' efficiency without replacing human decision-making.

Google’s Gemini to Power Waymo Robotaxis

Waymo is advancing its autonomous vehicle capabilities using Google’s Gemini model in its new "End-to-End Multimodal Model for Autonomous Driving" (EMMA). EMMA processes sensor data to predict vehicle trajectories and navigate complex environments, allowing Waymo’s robotaxis to handle obstacles like animals and construction. 

This marks a shift from traditional autonomous systems, which rely on separate modules for perception, mapping, and planning, to a single integrated model. However, EMMA currently has limitations, like difficulty processing 3D data, and Waymo notes further research is needed before it can deploy the model at scale.

AI Drives Google’s Q3 Success

Google’s Q3 earnings highlight growth in Search, Cloud, and YouTube, largely driven by advancements in AI. CEO Sundar Pichai emphasizes Google’s AI “full stack approach,” focusing on infrastructure, research, and extensive user reach. Major developments include Gemini AI models, deployed across Google platforms, and improved coding efficiency through AI. 

Google Cloud achieved strong growth with increased customer adoption, while YouTube saw record revenue growth due to ads and subscriptions. Platform innovations, such as Gemini integration on Android, and Waymo’s expansion in autonomous driving, underscore Google’s ongoing AI investment and focus on enhancing user experience and business productivity.

🧠RESEARCH

CLEAR: Character Unlearning in Textual and Visual Modalities

CLEAR, a new benchmark for assessing multimodal unlearning (MMU) in deep learning models, helping remove sensitive information across both text and images. CLEAR tests 10 methods for MMU and explores solutions to preserve model performance while improving privacy. It includes 200 fictional profiles and 3,700 paired images and questions.

SocialGPT: Prompting LLMs for Social Relation Reasoning via Greedy Segment Optimization

The SocialGPT framework leverages vision and language models to identify social relationships (like friends or colleagues) from images by translating visuals into text and then reasoning with language models. Using Greedy Segment Prompt Optimization (GSPO), SocialGPT achieves efficient, interpretable results without extra training, enhancing performance through automated prompt refinement.

AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions

AutoKaggle introduces a collaborative framework to automate data science tasks, enabling efficient workflows through a multi-agent system. It integrates automated code execution, debugging, and unit testing, allowing users to refine each phase. Tested on Kaggle competitions, AutoKaggle achieved high scores in data processing, enhancing productivity by automating repetitive data science tasks.

Robots Pre-train Robots: Manipulation-Centric Robotic Representation from Large-Scale Robot Dataset

Manipulation Centric Representation (MCR), a framework for training robots using large-scale robotic data instead of human videos. MCR improves robot learning by pre-training on dynamic task-specific data, achieving better task success rates. Tested in simulations and on a UR5e robotic arm, MCR significantly outperformed baseline methods, enhancing real-world task efficiency.

DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curation

DreamClear addresses real-world image restoration by combining GenIR, a privacy-safe data curation pipeline, with a powerful Diffusion Transformer-based model. GenIR creates a high-quality dataset of one million images without privacy risks, while DreamClear restores images photorealistically across diverse degradation types using adaptable restoration techniques. This dual strategy significantly improves real-world image restoration capabilities.

🛠️TOP TOOLS

Capsule -Aa video editor made for enterprise

PodLM - Turn Any Content into AI Podcast

Twill - Delivering Intelligent Healing with Sequences

Canonical AI - Improve Your AI Voice Assistant Quality

Sana AI - Your AI assistant for work

📲SOCIAL MEDIA

🗞️MORE NEWS

• Elon Musk predicts that by 2040, there will be over 10 billion humanoid robots available at prices ranging from $20,000 to $25,000. He shared this vision at the 8th Future Investment Initiative (FII) conference in Riyadh, Saudi Arabia. 

• Amazon has launched Rufus, an AI-powered shopping assistant, in beta across Europe. Rufus helps customers discover, research, and compare products by answering questions, providing tailored recommendations, and simplifying shopping within the Amazon app’s familiar experience.

• Creatio’s Energy 8.2 update enhances CRM automation with agentic AI, allowing non-technical users to build and customize AI skills. Its streamlined, no-code platform boosts productivity by simplifying complex workflows and improving customer interactions across departments.

• Google’s InkSight AI turns handwritten notes into digital text, preserving personal style and cognitive benefits. This tool bridges the gap between traditional writing and digital advantages, supporting search, sharing, and organization across diverse languages and settings.

• A new study shows that large language models (LLMs) can detect their own mistakes by analyzing specific response parts. These insights could lead to improved error detection and mitigation techniques, especially in open-source models.