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AlphaProteo: A New AI System for Protein Design  A powerful tool for biological research In a recent paper published in Nature, researchers from DeepMind introduced AlphaProteo, a new AI system for protein design. AlphaProteo can design proteins that bind to specific target molecules, which could be helpful for drug discovery, disease understanding, and more. AlphaProteo is better than other methods at designing these proteins. In one experiment, AlphaProteo designed binders that were 10 times stronger than those designed by other methods. AlphaProteo is still under development, but it has the potential to revolutionize many areas of science. What is AlphaProteo? AlphaProteo is a deep learning system that was trained on a large dataset of protein structures. The system can learn the rules that govern how proteins fold and how they interact with other molecules. This allows AlphaProteo to design new proteins that have specific properties, such as the ability to bind to a particular ...

AI Apps: A New Tool for ADHD Management   In the ever-evolving landscape of technology, artificial intelligence (AI) is making waves in an unexpected area: helping individuals with Attention Deficit Hyperactivity Disorder (ADHD). Recent developments have shown that AI apps can be powerful allies for those struggling with the challenges of ADHD, offering support in organization, task management, and focus.   ## The AI Advantage   Take Becky Litvintchouk, for example. As an entrepreneur with ADHD, she found starting her own business, GetDirty, a daunting task. However, by leveraging an AI app called Claude, she was able to navigate complex contracts and create business plans with ease. The app's ability to summarize information and generate step-by-step plans based on her goals proved "massively instrumental" in her success.   Litvintchouk's experience is not unique. Many individuals with ADHD are turning to AI tools to help manage their symptoms and improve their prod...

As cyber threats become more sophisticated, AI is emerging as a powerful tool to augment the capabilities of security professionals. By automating routine tasks like threat detection, AI enables professionals to focus on more complex issues. AI-driven analytics can swiftly identify patterns and anomalies, reducing response times and increasing accuracy. Moreover, AI can assist in predicting potential threats by analyzing vast datasets, helping to proactively defend against attacks. However, the integration of AI is not without challenges. Security teams must remain vigilant against AI-driven attacks and ensure that AI systems are used ethically and transparently. Training and collaboration between AI and human experts are key to maximizing the benefits while minimizing risks. Conclusion AI is not a replacement for human expertise but a force multiplier. It enhances the ability of security professionals to protect organizations in an increasingly complex threat landscape. As...

Yahoo Finance highlights three AI stocks considered excellent long-term investments due to their strong growth potential in the rapidly evolving AI industry. The article emphasizes the importance of investing in companies that are leaders in AI innovation, have robust financials, and a clear strategy for integrating AI into their operations. The three companies mentioned as "no-brainer" investments are Nvidia, Alphabet (Google), and Microsoft . These companies are well-positioned to capitalize on the AI boom, making them attractive choices for investors. For more detailed information, you can check out the full article [here]( https://finance.yahoo.com/news/3-no-brainer-artificial-intelligence-100300300.html ).  

Pascal Biese Pascal Biese Using the power of LoRAs to... fact check?! Researchers have found a way to combine multiple reasoning LoRAs (Low-Rank Adaptations) to significantly improve the fact-checking capabilities of Large Language Models (LLMs). LoraMap is a new approach that learns the connections between different reasoning LoRAs, each trained on a specific dataset. Unlike existing methods like LoraHub (which linearly adds LoRA weights) or LoraConcat (which concatenates LoRAs and fine-tunes them), LoraMap preserves the original LoRA matrices and only learns the mapping between them. This allows the model to reason from diverse perspectives while avoiding the pitfalls of weight averaging or catastrophic forgetting. The results? LoraMap outperforms both LoraHub and LoraConcat on fact-checking tasks with significantly fewer parameters. Enabling LLMs to better distinguish between claims and contexts and leverage domain-specific knowledge is important if we wan...

How To Jump-Start Learning At Work   "There is a paradox at the heart of the new AI technologies. One the one hand, they make almost everything more efficient. ---- There is a downside, however. The use of these technologies can also inhibit the development of important job-related skills." The article discusses the paradox of AI technologies in the workplace, which boost efficiency but may hinder skill development. It suggests flipping the script by using AI to enhance learning, akin to mastery learning and tutoring in education. In business, AI tutors could improve training effectiveness, especially in complex topics like interpersonal skills. The article advises executives to prioritize learning alongside efficiency, allowing time for skill development, and to consider the long-term impacts of AI on employee growth.