Amazon’s continuous innovation has developed products integrated with machine learning and artificial intelligence, allowing these systems to be accessible to everyone. Bratin Saha, Amazon’s VP of Machine Learning, has helped to constantly advance the major brand’s AIML services along with work on their product strategies in order to better serve consumers.
##Amazon’s goal is to make machine learning available to all customers through their products
Amazon continues to make machine learning and AI accessible for its consumers in the products it launches. Because of Amazon, AIML is accessible at home, adopted by organizations for productivity and continuously advancing since its investments into tech.
##Amazon has been investing in AI for more than 20 years
The major brand invested in AI and machine learning more than 20 years ago. This move has allowed them to bring thousands of engineers and create products their consumers use daily including Alexa, Amazon Go and Prime.
##Machine learning and AI are being adopted across all spectrums of business
There isn’t an industry that hasn’t invested somewhat into AIML. With continuous innovations and growth, AIML will be consumed by everyone in any organization in the years to come.

Saha shares his thoughts on where machine learning and AI are headed with Amazon’s developments, why the brand’s services are the best in the business and more, on this week’s episode.

Key takeaways:

• Amazon’s goal is to make machine learning accessible to all consumers with their products
• AIML will become an aid to how people get insights as well as how to get more proactive recommendations to customers
• Machine learning is having a very broad uptick as it is being adopted across all spectrums of business

Uber, the innovative rideshare company that has taken transportation to new levels of accessibility, is continuously developing ways to make the world move more efficiently through technology. Acknowledging the importance of artificial intelligence, Uber appointed Zoubin Ghahramani, the brand’s Chief Scientist and VP for AI, to steadily focus on how AI can advance people’s daily needs.
##A lot of start-ups and tech companies started getting interested in AI about 10 years ago
Ghahramani started his career in academia focusing on artificial intelligence. As he noticed AI’s impactful transition from academia to the tech industry, he began to advise start-ups and big tech companies into understanding AI’s industrial landscape. Within this transition, he started his company, Geometric Intelligence, that was acquired by Uber.
##Uber has a different strategy than other brands when it comes to AI
A lot of major companies invest in AI for the virtual world whereas Uber invests in the physical world. The decisions machine learning is helping with really matter to people including whether they’re going to get to one place to another on time, can they make income off of Uber’s platform and are trips safe.
##Academia focus and industry focus are different
A challenge Ghahramani faced once working with Uber was learning if his focus in academia would be useful in the tech industry. Once learning he had to change his ideas of how AI could be impactful, he was able to help develop cutting edge ideas and implement them to deliver high-value products.

Key takeaways:

• To Uber, anything that goes from data to models and algorithms that makes predictions and optimized decisions counts in some way as a form of AI or machine learning
• The use of AI for the physical world is continuously developing to help make people’s lives safer and more efficient while optimizing the world, creating income opportunities and more

Data and decision making go hand in hand in today’s economy, making it important to gather desired information quickly to make the right moves. Amit Prakash, co-founder and CTO of ThoughtSpot, knows the importance of obtaining analytics from his times at Microsoft and Google. Now, Prakash and his team are advancing how analytics are generated and how quickly they can be obtained. ThoughtSpot, a technology company that produces business-intelligence analytics search software, is on track to becoming the analytics engine of the world.
##A search and data-driven analytics engine
ThoughtSpot automates the interesting insights a business needs. Data is a big deal in this economy and ThoughtSpot’s system is making it more accessible at a faster rate with artificial intelligence and machine learning.
##ThoughtSpot has rethought what the architecture of a modern BI tool should be
Now, businesses are able to obtain data and make decisions much faster because of this system. Previously, systems took weeks to months to compile data whereas ThoughtSpot uses AI and machine learning to obtain data in minutes.
##ThoughtSpot has gotten really good at solving large problems at large enterprises
ThoughtSpot is being used in very meaningful ways at pretty much any large enterprise in any vertical. For example, one of the world’s largest retailers is using ThoughtSpot to optimize its decision cycles. Before, they would make decisions once a month making it harder to compete with Amazon where decisions were made much faster. After introducing ThoughtSpot, the retailer’s decision cycle went down from a month to less than an hour.

Listeners interested in learning more about ThoughtSpot can follow their progress on their site, ThoughtSpot.com.

Key takeaways:

• As more and more companies enter the digital age, competition becomes fiercer and more cutthroat. Companies are required to adapt faster and faster to stay ahead, thus it is becoming imperative to be able to search across company databases for instantaneous answers to important questions.
• ThoughtSpot is building a category-leading analytics and search platform for companies to ask questions in natural language and retrieve immediate answers. For example, with ThoughtSpot you can ask, “what are the quarterly sales by brand and by store?” without having to run complicated queries across multiple data sources.