Adobe’s New AI Assistant Manages Your Docs
Plus: Aria's recordings is fueling speech recognition, Penn's AI chip runs on light
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 215th edition of The AI Edge newsletter. This edition brings you Adobe’s new AI assistant and launch of CAVA lab.
And a huge shoutout to our amazing readers. We appreciate you😊
In today’s edition:
📃Adobe’s new AI assistant manages your docs
🎤 Meta released Aria recordings to fuel smart speech recognition
🔥 Penn's AI chip runs on light, not electricity
📚 Knowledge Nugget: How well can AI imitate a 17th century doctor? by
Let’s go!
📃 Adobe’s new AI assistant manages your docs
Adobe launched an AI assistant feature in its Acrobat software to help users navigate documents. It summarizes content, answers questions, and generates formatted overviews. The chatbot aims to save time working with long files and complex information. Additionally, Adobe created a dedicated 50-person AI research team called CAVA (Co-Creation for Audio, Video, & Animation) focused on advancing generative video, animation, and audio creation tools.
While Adobe already has some generative image capabilities, CAVA signals a push into underserved areas like procedurally assisted video editing. The research group will explore integrating Adobe's existing creative tools with techniques like text-to-video generation. Adobe prioritizes more AI-powered features to boost productivity through faster document understanding or more automated creative workflows.
Why does this matter?
Adobe injecting AI into PDF software and standing up an AI research group signals a strategic push to lead in generative multimedia. Features like summarizing documents offer faster results, while envisaged video/animation creation tools could redefine workflows.
🎤 Meta released Aria recordings to fuel smart speech recognition
Meta has released a multi-modal dataset of two-person conversations captured on Aria smart glasses. It contains audio across 7 microphones, video, motion sensors, and annotations. The glasses were worn by one participant while speaking spontaneously with another compensated contributor.
The dataset aims to advance research in areas like speech recognition, speaker ID, and translation for augmented reality interfaces. Its audio, visual, and motion signals together provide a rich capture of natural talking that could help train AI models. Such in-context glasses conversations can enable closed captioning and real-time language translation.
Why does this matter?
By capturing real-world sensory signals from glasses-framed conversations, Meta bridges the gaps AI faces to achieve human judgment. Enterprises stand to gain more relatable, trustworthy AI helpers that feel less robotic and more attuned to nuances when engaging customers or executives.
🔥 Penn's AI chip runs on light, not electricity
Penn engineers have developed a photonic chip that uses light waves for complex mathematics. It combines optical computing research by Professor Nader Engheta with nanoscale silicon photonics technology pioneered by Professor Firooz Aflatouni. With this unified platform, neural networks can be trained and inferred faster than ever.
It allows accelerated AI computations with low power consumption and high performance. The design is ready for commercial production, including integration into graphics cards for AI development. Additional advantages include parallel processing without sensitive data storage. The development of this photonic chip represents significant progress for AI by overcoming conventional electronic limitations.
Why does this matter?
Artificial intelligence chips enable accelerated training and inference for new data insights, new products, and even new business models. Businesses that upgrade key AI infrastructure like GPUs with photonic add-ons will be able to develop algorithms with significantly improved accuracy. With processing at light speed, enterprises have an opportunity to avoid slowdowns by evolving along with light-based AI.
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Knowledge Nugget: How well can AI imitate a 17th century doctor?
In the exploration of historical simulations using AI,
tests the capabilities of custom GPT-4 and Google's Gemini model by simulating a 17th-century physician's advice for the ailments of Arcadio Huang, a Chinese traveler in 1710s Paris. The custom GPT-4 called “1690s Physician” responds convincingly in the persona of a 1690s physician, diagnosing Huang's symptoms of weakness, fatigue, and spitting blood as a potential lung ailment. The prescribed treatment includes venesection, herbal remedies, dietary and lifestyle adjustments, aligning with historical medical practices. The AI performs well, considering the historical context and language.
However, when testing Google's Gemini, despite showing situational awareness and acknowledging Huang's origins, the model falls short in adopting the 1690s-style speech patterns and language recommended by the author. The response, while providing relevant advice, lacks the authenticity of a 17th-century physician, using modern language and suggesting practices contrary to historical medical norms. This comparison highlights the flexibility of AI models in historical simulations and raises questions about their adaptability to specific contexts and linguistic differences.
Why does this matter?
This experiment shows that improving AI's ability to model historical contexts leads to more creative bots. Just as learning about past medical practices grew doctors' skill sets for centuries, authentically simulating outdated worldviews trains AI on "common sense" and judgment. If bots can convincingly adopt past mindsets, they can relate easily to diverse humans. With these simulation techniques, AI assistants can understand context better and tailor communications accordingly.
What Else Is Happening❗
🖱 Brain chip: Neuralink patient moves mouse with thoughts
Elon Musk announced that the first human to receive a Neuralink brain chip has recovered successfully. The patient can now move a computer mouse cursor on a screen just by thinking, showing the chip's ability to read brain signals and control external devices. (Link)
💻 Microsoft develops server network cards to replace NVIDIA
Microsoft is developing its own networking cards. These cards move data quickly between servers, seeking to reduce reliance on NVIDIA's cards and lower costs. Microsoft hopes its new server cards will boost the performance of the NVIDIA chip server currently in use and its own Maia AI chips. (Link)
🤝 Wipro and IBM team up to accelerate enterprise AI
Wipro and IBM are expanding their partnership, introducing the Wipro Enterprise AI-Ready Platform. Using IBM watsonx AI, clients can create fully integrated AI environments. This platform provides tools, language models, streamlined processes, and governance, focusing on industry-specific solutions to advance enterprise-level AI. (Link)
📱 Telekom's next big thing: an app-free AI Phone
Deutsche Telekom revealed an AI-powered app-free phone concept at MWC 2024, featuring a digital assistant that can fulfill daily tasks via voice and text. Created in partnership with Qualcomm and Brain.ai, the concierge-style interface aims to simplify life by anticipating user needs contextually using generative AI. (Link)
🚨 Tinder fights back against AI dating scams
Tinder is expanding ID verification, requiring a driver's license and video selfie to combat rising AI-powered scams and dating crimes. The new safeguards aim to build trust, authenticity, and safety, addressing issues like pig butchering schemes using AI-generated images to trick victims. (Link)
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