MindEye2: AI Mind Reading from Brain Activity
Plus: Nvidia NIM enables faster deployment of AI models, Microsoft hires DeepMind co-founder to lead a new AI division.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 235th edition of The AI Edge newsletter. This edition brings you “MindEye2: AI Mind Reading from Brain Activity.”
And a huge shoutout to our incredible readers. We appreciate you😊
In today’s edition:
🧠 MindEye2: AI Mind Reading from Brain Activity
🚀 Nvidia NIM enables faster deployment of AI models
🤖 Microsoft hires DeepMind co-founder to lead a new AI division
💡 Knowledge Nugget: The Two Faces of AI: Empowering Hackers And Defenders Alike by
Let’s go!
MindEye2: AI mind reading from brain activity
MindEye2 is a revolutionary model that reconstructs visual perception from brain activity using just one hour of data. Traditional methods require extensive training data, making them impractical for real-world applications. However, MindEye2 overcomes this limitation by leveraging shared-subject models. The model is pretrained on data from seven subjects and then fine-tuned with minimal data from a new subject.
By mapping brain activity to a shared-subject latent space and then nonlinear mapping to CLIP image space, MindEye2 achieves high-quality reconstructions with limited training data. It performs state-of-the-art image retrieval and reconstruction across multiple subjects within only 2.5% of the previously required training data, reducing the training time from 40 to just one hour.
Why does it matter?
MindEye2 has the potential to revolutionize clinical assessments and brain-computer interface applications. This remarkable achievement also holds great promise for neuroscience and opens new possibilities for understanding how our brains perceive and process visual information. It can also help develop personalized treatment plans for neuro patients.
Nvidia NIM enables faster deployment of AI models
NVIDIA has introduced NVIDIA NIM (NVIDIA Inference Microservices) to accelerate the deployment of AI applications for businesses. NIM is a collection of microservices that package essential components of an AI application, including AI models, APIs, and libraries, into a container. These containers can be deployed in environments such as cloud platforms, Linux servers, or serverless architectures.
NIM significantly reduces the time it takes to deploy AI applications from weeks to minutes. It offers optimized inference engines, industry-standard APIs, and support for popular software and data platform vendors. NIM microservices are compatible with NVIDIA GPUs and support features like Retrieval Augmented Generation (RAG) capabilities for enhanced enterprise applications. Developers can experiment with NIM microservices for free on the ai.nvidia.com platform, while commercial deployment is available through NVIDIA AI Enterprise 5.0.
Why does it matter?
With NIM, Nvidia is trying to democratize AI deployment for enterprises by abstracting away complexities. This will enable more developers to contribute to their company's AI transformation efforts and allow businesses to run AI applications almost instantly without specialized AI expertise.
Microsoft hires DeepMind co-founder to lead a new AI division
Mustafa Suleyman, a renowned co-founder of DeepMind and Inflection, has recently joined Microsoft as the leader of Copilot. Satya Nadella, Microsoft's CEO, made this significant announcement, highlighting the importance of innovation in artificial intelligence (AI).
In his new role as the Executive Vice President and CEO of Microsoft AI, Mustafa will work alongside Karén Simonyan, another talented individual from Inflection who will serve as Chief Scientist. Together, they will spearhead the development and advancement of Copilot and other exciting consumer AI products at Microsoft. Mustafa and his team's addition to the Microsoft family brings a wealth of expertise and promises groundbreaking advancements in AI.
Why does it matter?
Mustafa Suleyman's expertise in AI is expected to contribute to the development of innovative consumer AI products and research at Microsoft, furthering its mission to bring the benefits of AI to people and organizations worldwide. With DeepMind's founder now at the helm, the AI race between Microsoft, Google, and others became even more intense.
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Knowledge Nugget: The Two Faces of AI: Empowering Hackers And Defenders Alike
In this article,
explores the impact of Generative AI on cybersecurity. The author emphasizes AI's dual nature, empowering hackers and enabling defenders to strengthen their security measures. It also emphasizes the financial and operational impact of cyberattacks, including direct financial losses and damage to brand reputation.The democratization of access to powerful computational tools through Generative AI has allowed smaller entities and individuals to participate in technological advancements. However, this also allows cybercriminals to employ AI to automate and refine their strategies, creating sophisticated malware that can bypass traditional security measures.
Why does it matter?
Generative AI is a dual tool for innovation and a weapon for hackers. So, a proactive approach to cybersecurity is needed, leveraging AI for defense, emphasizing the need for investment in security measures, ongoing education, and ethical AI development. Lastly, industry collaboration is critical in mitigating cyber threats and fostering a safer digital environment.
What Else Is Happening❗
📞 Truecaller adds AI-powered spam detection and blocking for Android users
Truecaller has unveiled a new feature for its Android premium subscribers that uses AI to detect spam, even if unavailable on the Truecaller database, and block every call that doesn’t come from an approved contact. Truecaller hopes to add more premium subscribers to its list by adding this feature. However, this feature is not available for Apple users. (Link)
⚽ Google DeepMind’s new AI tool can analyze soccer tactics and offer insights
DeepMind has partnered with Liverpool FC to develop a new AI tool called TacticAI. TacticAI uses generative and predictive AI to help coaches determine which player will most likely receive the ball during corner kicks, whether a shot will be taken, and how to adjust player setup. It aims to revolutionize soccer and help the teams enhance their efficiency. (Link)
🎬 Pika Labs introduces sound effects for its gen-AI video generation
Pika Labs has now added the ability to create sound effects from a text prompt for its generative artificial intelligence videos. It allows for automatic or custom SFX generations to pair with video outputs. Now, users can make bacon sizzle, lions roar, or add footsteps to the video of someone walking down the street. It is only available to pro users. (Link)
🎮 Buildbox 4 Alpha enables users to create 3D video games from text prompts
Buildbox has released an alpha version of Buildbox 4. It's an AI-first game engine that allows users to create games and generate assets from text prompts. The alpha version aims to make text-to-game a distinct reality. Users can create various assets and animations from simple text prompts. It also allows users to build a gaming environment in a few minutes. (Link)
🤖 Nvidia adds generative AI capabilities to empower humanoid robots
Nvidia introduced Project GR00T, a multimodal AI that will power future humanoids with advanced foundation AI. Project GR00T enables humanoid robots to input text, speech, videos, or even live demos and process them to take specific actions. It has been developed with the help of Nvidia’s Isaac Robotic Platform tools, including an Isaac Lab for RLHF. (Link)
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