Microsoft's Recent AI News

Microsoft has built itself up into a Cloud and Corporate Metaverse leader in recent years and that's staring to really show in its artificial intelligence ambitions. We have to give credit where it is due and Microsoft is doing more in the space than many analysts and even their own employees realize.

I write articles at the intersection of AI and technology on Substack called AISupremacy here.?

What is SynapseML?

• Microsoft has announced the release of?SynapseML, an open-source library that simplifies and speeds up the creation of machine learning (ML) pipelines.
• SynapseML can be used for building scalable and intelligent systems to solve various types of challenges, including anomaly detection, computer vision, deep learning, form and face recognition, gradient boosting, microservice orchestration, model interpretability, reinforcement learning and personalization, search and retrieval, speech processing, text analytics and translation.
• SynapseML is a powerful platform for building production-ready distributed machine learning pipelines. It bridges the gap between several existing ML frameworks and Microsoft algorithms in order to create one scalable API that works across Python and R Language-based platforms like Scala or Java.

To quote Microsoft itself, we are entering a time when business leaders across the world are increasingly asking themselves a few questions: How can my company use AI effectively? Are we exploring the right business opportunities?

Microsoft as a Corporate Metaverse leader is positioning itself as digital transformation foundry. Even if AI's path isn't a clear or straightforward one, the technologies are changing and developing all the time. It can be difficult to know how to structure an approach to AI innovation.

You can check Microsoft's AI blog here.

In order to build a machine learning pipeline, you need more than just coding skills. In fact, many developers find composing tools from different ecosystems requires considerable code, and frameworks aren’t designed for the task at hand-building servers in this case.

What is the Future of Datascience?

The growing pressure on data science teams to get more machine learning models into use and the fact that many companies still find themselves deploying AI within a reasonable amount of time despite these rising trends should not go unheeded.

SynapseML eliminates the hassle of working with multiple different ML learning frameworks by providing a single API that is scalable, data-agnostic and language-neutral. It’s designed to help developers focus on high-level structures in their datasets instead of having them get bogged down trying to implement all these individual networks one at a time for every possible task or application type imaginable.

With the integration of a unified API, many tools are standardized, including frameworks and algorithms. This streamlines distributed machine learning experience for all users. It enables developers to write ML frameworks for use cases that require more than one framework.

These features make it easy and quick, which is perfect for quick web supervised learning or search engine creation. It can also train models on a single node and scalable cluster of computers without wasting resources.

This will help them quickly scale up their work with minimal overhead costs. The API can be used in a variety of programming languages to abstract over database access, file systems and cloud data stores.

Github: https://github.com/microsoft/SynapseML

I write articles at the intersection of AI and technology on Substack called AISupremacy here.?

Business Adoption of AI is Heating Up

Microsoft is scaling up its AI software services as it matures in the Cloud and integrates its products in the Corporate Metaverse.

There are significant bottlenecks in AI adoption however. While AI adoption and analytics?continue to rise, an?estimated?87% of data science projects never make it to production. According to Algorithmia’s recent?survey, 22% of companies take between one and three months to deploy a model so it can deliver business value, while 18% take over three months.

So what happens in reality? As Microsoft explains on the project’s?website, SynapseML expands?Apache Spark, the open source engine for large-scale data processing, in several new directions.

For cutting-edge news of Microsoft AI in action go here.

SynapseML makes things easier and integrates tools better. SynapseML introduces new algorithms for personalized recommendation and?contextual bandit reinforcement learning?using the Vowpal Wabbit framework, an open source machine learning system library originally developed at Yahoo Research.

Microsoft AI Research is Improving

I think Microsoft’s interest in GPT-3 reflects a growing use of transformer-based deep learning models. As more organizations are using these models because they perform better understanding semantic relationships.

One of the problems Microsoft has found when relating transformer-based deep learning is that nuances in relationships are often beyond the models. Microsoft Research has now created a neural network that nearly matches the capabilities of GPT-3.

In March, 2021 Microsoft's announcement of its?$19.7 billion acquisition?of Nuance, a company that provides speech recognition and conversational AI services really shows how serious they are about AI.

Microsoft is increasingly introducing what it calls a "set of natively integrated AI experiences" across Microsoft 365 that will go beyond the current AI capabilities already baked into some Office apps. While Microsoft didn't make a competitive smart assistant or smart speaker for the office, it's keeping up in new ways.

Nuance had built several of its products on top of Microsoft’s Azure cloud. And Microsoft had been using Nuance’s Dragon service in its Cloud for Healthcare solution, which launched last year in the midst of the pandemic. Microsoft has really no choice but to acquire Doximity.

It's the LinkedIn for Doctors in a real sense. Doximity is an online networking service for medical professionals that would be a bridge between Nuance and LinkedIn.?

I write articles at the intersection of AI and technology on Substack called AISupremacy here.?