❇️ NVIDIA Continues Pushing AI’s Boundaries
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📝 EditorialIn the last few years, NVIDIA has ranked among the top companies advancing AI research and development. With its unique approach that encompasses both hardware and software, NVIDIA has been at the forefront of several major milestones in the AI industry. NVIDIA conferences are among the most followed events by the data science community, and they rarely disappoint. During its latest GTC conference, NVIDIA announced major releases in both AI software and hardware technologies. The AI announcements at GTC show NVIDIA’s depth across every area of AI. On the software side, NVIDIA announced new cloud services such as NeMo for large-scale language models, Omniverse ACE for intelligent avatars, and BioNeMo computational biology. On the hardware end, NVIDIA introduced its new ADA architecture, which includes an improved streaming multiprocessor as well as new Tensor Core with the Hopper FP8 Transformer Engine and 1.4 petaflops of Tensor processor power. NVIDIA also announced a number of architectures based on ADA, such as chips optimized for virtual worlds, computational inference, recommendation models, and many others. Continuing its innovation in areas such as self-driving vehicles and robotics, NVIDIA announced Thor, a new 2,000 teraflops of performance and will become the hardware of choice for many applications in those domains. GTC provided another window to witness NVIDIA’s astonishing reach in the AI space. Many of the innovations uncovered during GTC are already powering mission-critical applications across many industries. These days, we can safely say that NVIDIA is synonymous with large-scale AI. 🔺🔻TheSequence Scope – our Sunday edition with the industry’s development overview – is free. To receive high-quality content about the most relevant developments in the ML world every Tuesday and Thursday, please subscribe to TheSequence Edge 🔺🔻 🗓 Next week in TheSequence Edge: Edge#229: we introduce VQGAN + CLIP architecture; discuss the original VQGAN+CLIP paper; explore the VQGAN+CLIP implementations. Edge#230: we deep dive into how Amazon scaled Alexa to 1000 languages Subscribed 🗺 Take the Survey!Let’s create an objective landscape of the ML Value Chain together. You’ve probably seen some AI/ML companies’ landscapes before. They are typically assembled by either analyst firms, media, or VC firms. But we trust that TheSequence’s audience only can shape an accurate landscape of the ML Value Chain. Participate and be the first to receive this super helpful research shaped by you! Now, let’s review the most important developments in the AI industry this week 🔎 ML ResearchWhisper OpenAI published a paper detailing Whisper, a neural network that achieved human-level accuracy in speech recognition →read more Sparrow DeepMind published a paper introducing Sparrow, a reinforcement learning model used to build safer conversational agents →read more View Synthesis with Transformers Google Research published a paper discussing a transformer-based model for view synthesis or the ability to recreate a scene from several images →read more Sounding More Human IBM Research published a paper detailing a technique that combines speech recognition and storytelling to make conversational agents sound more human →read more 🤖 Cool AI Tech ReleasesNeMo LLM Service NVIDIA announced NeMo LLM Service, a cloud service for building and training mega large language models →read more Omniverse ACE NVIDIA announced Omniverse ACE and AI microservices, a platform that enables the development of AI-powered avatars →read more Other NVIDIA Announcements There were too many NVIDIA AI announcements this week to cover individually →read the summary of the announcements TensorStore Google Research open-sourced TensorStore, a C++ and Python library designed for high dimensional array storage and manipulations →read more LAVIS Salesforce Research open-sourced LAVIS, a deep learning library to streamline language-vision model research and implementation →read more 🛠 Real World MLVehicle Routing at Walmart Walmart Global Technology group discusses the ML architecture for vehicle and container routing for grocery delivery →read more 💸 Money in AIML&AI
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👾 Edge#228: How Amazon is Improving BERT-Based Models Used in Alexa
Thursday, September 22, 2022
Recently Amazon Research published three papers about BERT-based models
📝 Guest post: Unlock the Power of BLOOM With the Broadest Range of GPUs Served On-Demand*
Wednesday, September 21, 2022
In this guest post, CoreWeave introduces BLOOM deploy on their platform and guides you through their arsenal of GPUs to ensure you find the compute that delivers the best possible performance-adjusted
📃➡️🖼 Edge#227: Autoregressive Text-to-Image Models
Tuesday, September 20, 2022
+Google's Parti; +MS COCO
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Monday, September 19, 2022
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Sunday, September 18, 2022
Weekly news digest curated by the industry insiders
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