🗣🗣🗣Another Amazing Week for Large Language Models
Was this email forwarded to you? Sign up here 🗣🗣🗣Another Amazing Week for Large Language ModelsWeekly news digest curated by the industry insiders📝 EditorialNatural language understanding (NLU) has been, by far, the fastest growing area of deep learning. Regularly, we read about massive NLU models reaching new milestones across different language tasks. This week, we had a fresh taste of the progress with models published by Meta AI and Alexa AI. In Edge#3, we covered Meta’s release of BlenderBot, a chatbot that could converse about almost any topic. The magic of BlenderBot is its ability to rapidly mine the internet and incorporate domain knowledge in conversations making the interactions more natural. BlenderBot is also able to collect feedback and upgrade itself. This week, Meta AI open-sourced BlederBot 3, a new 175 billion parameter version that achieves over 30% improvement compared to its predecessors across different conversational tasks. Meta AI released a live demo of BlenderBot 3, allowing users to interact with the chatbot and contribute to its training. Amazon’s Alexa AI team is another AI lab that has been pushing the boundaries of NLU models. That is not surprising considering that Alexa-powered devices are one of the world’s most active AI conversational environments. This week, Alexa AI unveiled AlexaTM, a 20 billion parameter model that uses few-shot learning to master tasks in new languages with just a few training examples. AlexaTM topped GPT-3 in many tasks in low-resource languages. The pace of progress in NLU research is astonishing and never boring. The models released this week by Meta AI and Alexa AI challenge the imagination of the new frontiers for NLU models. 🔺🔻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#215: we discuss Pre-Train Model Testing; overview the pillars of robust machine learning; explore Great Expectations. Edge#216: we overview Gato, DeepMind’s new Super Model that can generalize across multiple tasks on different domains. Now, let’s review the most important developments in the AI industry this week 🔎 ML ResearchMulti-Domain Neural Architecture Search Google Research published a paper about a multi-path neural architecture search technique to create unified architecture across multiple domains →read more on the Google Research blog AlexaTM Amazon Research unveiled AlexaTM, a 20 billion parameter model that achieves state-of-the-art performance in several few-shot learning language benchmarks →read more on the Amazon Research blog ViTDet Meta AI published a paper detailing ViTDet, a hierarchical vision transformer optimized for detecting uncommon object classes →read more on the Meta AI blog Enhancing Backpropagation Google Research published a paper introducing a new technique to train neural networks improving upon the iconic backpropagation algorithm →read more on the Google Research blog 🤖 Cool AI Tech ReleasesBlenderBot 3 Meta AI released BlenderBot 3, a 175 billion parameter chatbot that can converse about almost any topic →read more on the Meta AI blog auton-survival Carnegie Mellon University open-sourced auton-survival, a framework for counterfactual estimation, regression, and evaluation of time-to-event data →read more on the Carnegie Mellon University blog 🛠 Real World MLPricing at Lyft Lyft unveils some details about the data and ML infrastructure used for pricing in its transportation marketplace →read more on the Lyft Engineering blog 💸 Money in AIAI-powered
Acquisition
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📝 Guest post: Auto Labeling to Power Insurance Automation: Quickly Label Quality Datasets*
Friday, August 5, 2022
In this guest post, Superb AI shares a use case with their client Autonet that focuses on streamlining the claims experience in the auto insurance industry, using computer vision, AI, and domain
🗺 Edge#214: NLLB-200, Meta AI’s New Super Model that Achieved New Milestones in Machine Translations Across 200 L…
Thursday, August 4, 2022
One of the most important achievements to bring machine translation to low-resource languages
🩺 Edge#213: Testing Trained Models
Tuesday, August 2, 2022
the fundamental types of tests that can be applied to trained models +how Meta uses Bayesian Optimization for A/B tests +TensorFlow's What-If Tool
📝 Guest post: Using AI to Learn a Disentangled Gait Representation for Versatile Quadruped Locomotion*
Monday, August 1, 2022
The Oxford Robotics Institute (ORI) is built from collaborating and integrated groups of researchers, engineers and students all driven to change what robots can do for us. The ORI is interested in a
🧬 DeepMind’s AlphaFold Database
Sunday, July 31, 2022
Weekly news digest curated by the industry insiders
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