The Sequence Scope: Making Sense of Microsoft’s Recent Machine Learning Announcements
Weekly newsletter that discusses impactful ML research papers, cool tech releases, the money in AI, and real-life implementations.
The Sequence Scope is a summary of the most important published research papers, released technology and startup news in the AI ecosystem in the last week. This compendium is part of TheSequence newsletter. Data scientists, scholars, and developers from Microsoft Research, Intel Corporation, Linux Foundation AI, Google, Lockheed Martin, Cardiff University, Mellon College of Science, Warsaw University of Technology, Universitat Politècnica de València and other companies and universities are already subscribed to TheSequence.
TheSequence explains the main machine learning concepts and keeps you up-to-date with the most relevant projects and…
📝 Editorial: Making Sense of Microsoft’s Recent Machine Learning Announcements
Microsoft and Amazon have embarked on a frantic race for dominating the cloud machine learning(ML) ecosystem. Every year, both technology giants release dozens of new additions to their ML platforms. Last week, it was Microsoft’s turn to dominate the news. During its Ignite conference, Microsoft unveiled an overwhelming number of new ML services that expand the capabilities of its already impressive ML offering. Here is a quick summary of what Microsoft announced this week:
- Azure Percept: A new service to enable AI capabilities on edge devices.
- Azure Arc: A service to enable ML models to run in multi-cloud infrastructures.
- Azure Synapse: A service for end-to-end big data analytics. The release includes complementary services such as Synapse Link, for integrating CosmosDB, and Synapse Pathway, which integrates legacy data warehouse technologies with Synapse.
- Azure Purview: A new service for data governance and management.
- Azure Cognitive Search: A new service that enables semantic search capabilities as an API model.
As you can see, this is an impressive series of releases and one that addresses some of the hottest trends in modern ML applications. When it comes to ML, Microsoft continues to innovate at a very impressive pace and it’s becoming one of the most complete suites of ML technologies in the market.
🗓 Next week in TheSequence Edge:
Edge#69: search strategies in neural architecture search; Google’s evolved transformer that is a killer combination of transformers and NAS; Microsoft’s neural network intelligence — the most impressive AutoML framework you have ever heard of.
Edge#70: deep dive into how LinkedIn uses typed features to accelerate machine learning experimentation at scale
🔎 ML Research
Facebook AI Research (FAIR) published a super insightful post about the current state of self-supervised learning models ->read more on FAIR blog
Billion-Parameter Self-Supervised Model
Facebook AI Research (FAIR) published a paper outlining SEER, a new billion-parameter, self-supervised learning model that achieves state-of-the-art performance in different image classification tasks ->read on FAIR blog
How Bing Powers Azure Cognitive Service Search
Microsoft Research published a very interesting blog post about how Bing’s semantic search capabilities are powering the Azure Cognitive Search service at scale ->read more Microsoft Research blog
OpenAI published a fascinating paper discussing how neurons inside their CLIP model are able to react to the same concept via texts or images ->read more on OpenAI blog
🤖 Cool AI Tech Releases
Microsoft announced Azure Percept, a new platform for edge AI solutions ->read more in this blog post from the Azure team
Microsoft unveiled the first public preview of Azure Arc, a service to run machine learning models in on-premised, hybrid or multi-cloud infrastructures ->read more in this blog post from the Azure team
Azure Purview and Synapse
Microsoft also unveiled public previews of Azure Purview, a service for data governance, and Azure Synapse, services for large-scale analytics ->read more in this blog post from the Azure team
AWS DeepRacer Divisions
Amazon announced new open and pro divisions for the AWS DeepRacer League, a challenge for reinforcement learning models in autonomous vehicles ->read more in this blog post from the AWS team
AWS SageMaker RL Components for Kubeflow
Amazon announced SageMaker Reinforcement Learning Kubeflow Components, supporting AWS RoboMaker, a cloud robotics service, for orchestrating robotics ML workflows->read more in this blog post from the AWS team
💸 Money in AI
For ML engineers and data scientists:
- Feature engineering platform Kaskada raised $8 million in a funding round. They claim that their platform is the first ML platform for data scientists that focuses on the feature engineering and feature serving experience. The platform includes a collaborative interface for data scientists and is powered by proprietary data infrastructure for computing across event-based data and serving features in production.
- Quality data annotation provider Quality Match raised a $6 million seed round. The startup improves ML models through optimized datasets with controlled annotation quality.
- Open-source data-integration platform Airbyte raised $5.2 million in seed funding. Their mission is to become the open-source standard for data integration and data movement, and to commoditize it.
AI & ML business implementation
- E-commerce startup Snapcommerce raised $85 million in a funding round. Their AI-powered recommendations engine generates and delivers personalized deal recommendations for each unique customer.
- Digital-first dental insurer Beam Dental raised $80 million in a Series E round. Using AI and ML, Beam rewards those who brush and floss more with lower rates, incentivizing policyholders to maintain better wellness overall.
- Sales data automation platform Dooly raised $20 million in funding. With their AI-based tools, Dooly revolutionizes the relationship between data software and a salesman by automating manual data entry and sales software data updates.
- Healthcare API provider Health Gorilla raised $15 million in a Series B round. Their AI-tools automatically identify key demographic information in each document ingested, normalize the data, and remove duplicate data so healthcare developers can easily integrate it into their own workflows.
- Data insights visualization startup Cipher Skin raised$5 million in a Series A round. The startup develops a network of wraparound sensors that capture movement and internal metrics from humans and objects to deliver meaningful, visualized insights.