Sora Showcases Jaw-dropping Geometric Consistency
Plus: Microsoft introduces Copilot for finance in Microsoft 365, and OpenAI and Figure team up to develop AI for robots
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 222nd edition of The AI Edge newsletter. This edition brings you Sora showcases jaw-dropping geometric consistency
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In today’s edition:
🪄Sora showcases jaw-dropping geometric consistency
🧑✈️Microsoft introduces Copilot for finance in Microsoft 365
🤖OpenAI and Figure team up to develop AI for robots
📚 Knowledge Nugget: The Chinese thought experiment is wrong for AI by
Let’s go!
Sora showcases jaw-dropping geometric consistency
Sora from OpenAI has been remarkable in video generation compared to other leading models like Pika and Gen2. In a recent benchmarking test conducted by ByteDanc.Inc in collaboration with Wuhan and Nankai University, Sora showcased video generation with high geometric consistency.
The benchmark test assesses the quality of generated videos based on how it adhere to the principles of physics in real-world scenarios. Researchers used an approach where generated videos are transformed into 3D models. Further, a team of researchers used the fidelity of geometric constraints to measure the extent to which generated videos conform to physics principles in the real world.
Why does it matter?
Sora’s remarkable performance in generating geometrically consistent videos can greatly boost several use cases for construction engineers and architects. Further, the new benchmarking will allow researchers to measure newly developed models to understand how accurately their creations conform to the principles of physics in real-world scenarios.
Microsoft introduces Copilot for finance in Microsoft 365
Microsoft has launched Copilot for Finance, a new addition to its Copilot series that recommends AI-powered productivity enhancements. It aims to transform how finance teams approach their daily work with intelligent workflow automation, recommendations, and guided actions. This Copilot aims to simplify data-driven decision-making, helping finance professionals have more free time by automating manual tasks like Excel and Outlook.
Copilot for Finance simplifies complex variance analysis in Excel, account reconciliations, and customer account summaries in Outlook. Dentsu, Northern Trust, Schneider Electric, and Visa plan to use it alongside Copilot for Sales and Service to increase productivity, reduce case handling times, and gain better decision-making insights.
Why does it matter?
Introducing Microsoft Copilot for finance will help businesses focus on strategic involvement from professionals otherwise busy with manual tasks like data entry, workflow management, and more. This is a great opportunity for several organizations to automate tasks like analysis of anomalies, improve analytic efficiency, and expedite financial transactions.
OpenAI and Figure team up to develop AI for robots
Figure has raised $675 million in series B funding with investments from OpenAI, Microsoft, and NVIDIA. It is an AI robotics company developing humanoid robots for general-purpose usage. The collaboration agreement between OpenAI and Figure aims to develop advanced humanoid robots that will leverage the generative AI models at its core.
This collaboration will also help accelerate the development of smart humanoid robots capable of understanding tasks like humans. With its deep understanding of robotics, Figure is set to bring efficient robots for general-purpose enhancing automation.
Why does it matter?
Open AI and Figure will transform robot operations, adding generative AI capabilities. This collaboration will encourage the integration of generative AI capabilities across robotics development. Right from industrial robots to general purpose and military applications, generative AI can be the new superpower for robotic development.
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Knowledge Nugget: The Chinese thought experiment is wrong for AI
In this article,
discusses how LLMs like ChatGPT have proven John Searle’s ‘Chinese Room’ thought experiment wrong. According to the argument, AI was believed never to obtain “Understanding” capabilities like humans. However, modern LLMs have been proving the entire argument wrong.Here are several critical aspects of AI and its ability to understand things like humans do:
LLMs like ChatGPT undermine Searle's argument by demonstrating conversational fluency and the ability to map words onto meaning.
LLMs can map words onto meaning, countering Searle's claim that AIs lack 'semantics'.
LLMs perform information processing like the human brain, suggesting a level of 'intentionality' in their responses.
The capabilities of LLMs raise questions about the traditional arguments against AI 'understanding' and prompt the need for new perspectives on the concept.
LLMs construct a complex semantic space with thousands of dimensions during their training phase
The vector assigned to a word by LLMs is functionally comparable to structures of information in the human brain that represent the word's meaning.
Further, it highlights that LLMs still have limitations in some forms of reasoning, but computer scientists are working on solutions.
Why does it matter?
Can machines really understand the world, or are they just pattern recognizers? This question is important for our relationship with AI. This article explores the evolving capabilities of LLMs and the need for continued exploration and new perspectives on intelligence. LLMs may be a stepping stone towards AGI.
What Else Is Happening❗
🤝Stack Overflow partners with Google Cloud to power AI
Stack Overflow and Google Cloud are partnering to integrate OverflowAPI into Google Cloud's AI tools. This will give developers accessing the Google Cloud console access to Stack Overflow's vast knowledge base of over 58 million questions and answers. The partnership aims to enable AI systems to provide more insightful and helpful responses to users by learning from the real-world experiences of programmers. (Link)
💻Microsoft unites rival GPU makers for one upscaling API
Microsoft is working with top graphics hardware makers to introduce "DirectSR", a new API that simplifies the integration of super-resolution upscaling into games. DirectSR will allow game developers to easily access Nvidia's DLSS, AMD's FSR, and Intel's XeSS with a single code path. Microsoft will preview the API in its Agility SDK soon and demonstrate it live with AMD and Nvidia reps on March 21st. (Link)
📈Google supercharges data platforms with AI for deeper insights
Google is expanding its AI capabilities across data and analytics services, including BigQuery and Cloud Databases. Vector search support is available across all databases, and BigQuery has the advanced Gemini Pro model for unstructured data analysis. Users can combine insights from images, video, audio, and text with structured data in a single analytics workflow. (Link)
🔍 Brave’s privacy-first AI-powered assistant is now available on Android
Brave's AI-powered assistant, Leo, is now available on Android, bringing helpful features like summarization, transcription, and translation while prioritizing user privacy. Leo processes user inputs locally on the device without retaining or using data to train itself, aligning with Brave's commitment to privacy-focused services. Users can simplify tasks with Leo without compromising on security. (Link)
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