Simone Di Somma’s Post

Latest video from Tesla AI and Robotics team starring Optimus. #Why could be a #success 🤝 #Synergy: Tesla's existing expertise in AI, particularly in computer vision and sensor fusion for self-driving cars, provides a strong foundation for developing Optimus. This existing technology can be adapted and leveraged for tasks like navigation, object recognition, and real-time decision-making in the robot. 📊 #Data: Tesla's vast amount of real-world data collected from its fleet of vehicles could be invaluable in training Optimus' AI models. This data can help the robot learn to navigate complex environments, interact with objects, and respond to unforeseen situations. 🌐 #Integration: Tesla's control over both hardware and software development allows for tight integration and optimization. This could lead to a more efficient and capable robot compared to those developed with separate hardware and software components. #Why could be a #failure 🧮 #Complexity: Developing a truly functional and useful humanoid robot is an incredibly complex challenge. Issues like dexterity, balance, and adaptability to diverse environments require significant breakthroughs in AI and robotics. Tesla's aggressive timelines might underestimate the intricacies involved. ⌛ #LimitedFocus: The video primarily showcases Optimus performing simple, repetitive tasks. While this demonstrates progress in robotics, it's unclear how Tesla plans to tackle the challenge of general intelligence. Without significant advancements in this area, Optimus' applicability might remain limited. 🖐🏼 #Ethical: The development of advanced humanoid robots raises ethical and societal concerns about job displacement, potential misuse, and the impact on human interaction. Tesla needs to proactively address these concerns and ensure responsible development and deployment of Optimus. #AI #Robotics

Andreessen Horowitz's recent report reveals that in 2023, the average #GenAI spend among 70 surveyed Fortune 500 companies was $7M, with projections to increase 2x to 5x by 2024. As #GenerativeAI shifts from experimental to production phases, the strategic value and investment in these technologies are on the rise. 🌐 Toward Open Source and Multi-Models 🌐 Enterprises increasingly embrace open-source models. Companies are prioritizing flexibility, customization, and control, diversifying their AI strategies to avoid vendor lock-in and better tailor technology to specific needs. 💼 Budget Reallocation and ROI tracking 💼 Businesses are transitioning GenAI spending from innovation-specific budgets to standard recurring allocations, underscoring a long-term commitment. Enterprises are also refining ROI metrics to quantify the impact As the enterprise landscape for GenAI continues to evolve, the opportunity for startups and service providers is expanding significantly.

🚨 In a twist that blurs reality with technology, fans and media were recently thrown into a frenzy by tracks attributed to Taylor Swift and Drake. These leaks, which neither artist has authenticated, may be sophisticated AI #deepfake. The ambiguity has sparked massive Reddit, Inc. threads, where fans dissect musical evidence, and meme videos simulating reactions from other artists, highlighting the confusion and debate surrounding the authenticity of celebrity media. Amidst this confusion, the industry is taking action through legislation and litigation to defend artists' rights. Initiatives like the ELVIS Act and various lawsuits against #AI firms for misuse. We live in a world where the line between the real and the fabricated is increasingly indistinct. How will we adapt to a reality where seeing—or hearing—is no longer believing? #TaylorSwift #Drake #ArtificialIntelligence #MusicIndustry #DigitalEthics

GPT-performance #AI model to your pocket 📱 Microsoft just unveiled a language model that rivals the capabilities of giants model such as GPT3.5 and Mixtral, but with a twist – it's small enough to run locally on your phone. 🤯 paper in the comment 👇 #Why is this a game-changer? #Privacy: Phi-3 eliminates the need for constant cloud connectivity. This also opens doors for privacy-focused AI applications #Cost: By reducing reliance on cloud computing resources, businesses can significantly lower operational costs associated #Offline: Imagine AI-powered applications that work seamlessly even without internet access. Phi-3 unlocks a new era of possibilities for mobile experiences. #How did they achieve this? Microsoft researchers focused on data optimization rather than simply scaling up model size or data used for the training. By carefully curating and filtering training data, they achieved exceptional performance with a compact model size.

Exploring 2024's global economic paradox of resilient growth amid rising geopolitical tensions and technological transformations and the role of #AI

Thanks to the B Heroes Founders Club for welcoming me into this dynamic network of advisors. It's an honor to collaborate and share my founder and technical expertise with such group! CC Carolina Montagna Tommaso Moraca

Sam Altman & Jony Ive's 1B #AI Startup 🚀 Sam Altman and Jony Ive are in talks to raise $1 billion in funding for their secretive Al-powered personal device startup, potentially leveraging OpenAl's advanced conversational 💡Al technology: The proposed device is expected to deliver an innovative user experience but will not resemble a traditional smartphone, showcasing a convergence of design expertise and Al innovation. 💰 Among the potential backers are Emerson Collective and Thrive Capital, with ties to OpenAI, hinting at strategic alignment with the startup's ambitious goals.

✨ Exciting news for the open source #GenAI community! 🤗 Hugging Face changes the Text-Generation-Inference (TGI) library license back to Apache 2.0 👉 Why is that a thing? Three reasons: 1. another boost to the. open source collaboration (more community) 2. easing codebase maintenance (less bugs, more performance) 3. expanding the HF open-source ML footprint (more adoption) A strategic step for future innovation and growth for the #ArtificalIntelligence ecosystem! Thanks Clem Delangue 🤗

#LLMs are as smart as the input we use to spark ⚡️ their reasoning power. This program by Pi School will let you master how to maximize the gain from each generative #AI model 🔥 #Audience: target are folks who want to approach LLMs for the first time

DeepMind's SAFE: automating fight against misinformation #Problem Large language models (LLMs) are changing the way we interact with information. But with great power comes great responsibility: ensuring the accuracy of information these models provide is crucial. #Solution SAFE (Search-Augmented Factuality Evaluator) tackles the challenge of LLM factual accuracy in long-form text. #How It works by creating multiple paraphrases of a question and then checking the LLMs' answers for consistency across these variations. This innovative approach exposes errors that might slip through traditional methods. #Why But why is this relevant for businesses? Here's how SAFE can have a significant impact: Search Accuracy: SAFE verifies info in search results, ensuring users get reliable answers. Customer Trust: SAFE helps businesses ensure accurate marketing and chatbots, building trust and loyalty. Education: SAFE empowers educational tools to verify information. Fight Fake News: SAFE helps reduce the spread of misinformation online. Google DeepMind's SAFE research holds potential for businesses across sectors. By ensuring factual accuracy and building trust