Self-driving cars and truck startup Cruise has actually just gotten a $2 billion infusion from Microsoft, General Motors, Honda, and institutional investors, according to a joint statement by Cruise, its owner GM, and Microsoft on Tuesday. The investment will bring Cruise’s valuation to $30 billion and make Microsoft a main partner.
Per Tuesday’s statement: “To unlock the capacity of cloud computing for self-driving automobiles, Cruise will take advantage of Azure, Microsoft’s cloud and edge computing platform, to commercialize its special autonomous vehicle solutions at scale. Microsoft, as Cruise’s preferred cloud provider, will also use Cruise’s deep industry knowledge to enhance its customer-driven item innovation and serve transportation business around the world through continued financial investment in Azure.”
So Cruise will get the much-needed funds to carry out research study and (potentially discounted) access to Microsoft’s cloud computing resources and move closer to its objective of releasing a purpose-built self-driving automobile.
However in the long run, Microsoft stands to get more from the deal. Not only will it get 2 really financially rewarding customers for its cloud business (Azure will also end up being GM’s preferred cloud supplier, per the announcement), however when seen in the wider context of Microsoft’s self-driving automobile strategy, “Cruise’s deep market expertise” will possibly give Microsoft a solid foothold in the future of the still-volatile self-driving cars and truck market.
At a time when most major tech business are interested in getting self-driving car start-ups or introducing their own efforts, Microsoft’s hands-off method could eventually turn it into a market leader.
Self-driving vehicles from the AI business viewpoint
Self-driving automobiles can be viewed as a specialized case within AI-driven services. Every business running on AI algorithms– particularly machine learning– should unite a few key pieces to have a viable organization design:
- Algorithms: The company must either utilize existing machine learning algorithms or research study brand-new architectures that fit the issue.
- Information: The business should have a sound facilities that consolidates disparate data sources. It must also have methods to gather and keep fresh data from customers to continue to maintain and tune its designs and keep an edge over competitors.
- Compute resources: The company will require access to large compute clusters and specialized hardware to train and upgrade its machine learning designs and supply cloud-based reasoning at scale.
- Talent: The business needs data researchers, information engineers, and machine learning engineers to develop and keep AI models and research new strategies.
Microsoft already has a strong AI stack and a complete range of products that fit into this classification. The company’s computer system vision service runs on machine knowing models developed by the business’s engineers. Microsoft’s Azure cloud has actually specialized hardware to both train the models and provide them at scale and in an affordable way.
Lots of business utilize Microsoft’