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What Will the Future of the AI and Machine Learning Industry Look Like?

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Read more about author Cory Hymel.

AI applications catering to the mass public are moving towards larger-scale use for enterprises, as big tech companies try to get into this new technology. As the use of AI proliferates in the future, tremendous amounts of computing power from cloud service providers are needed to operate these AI applications and unleash more of their potential.

Cloud services play an important role in streamlining and providing flexibility in the development of web and mobile applications through virtual server hosting and various services such as big data analytics and cloud computing.

With tech giants Amazon, Google, and Microsoft dominating the global cloud market – taking up 66% share from 50% in 2017 – what will AI and machine learning look like in the future? Is it good for AI to be run by the largest companies? Will it be good for innovation, and will it benefit the public? Are we headed toward an AI-fueled future controlled by corporations?

Let us seek to answer these questions and find out the potential benefits and pitfalls of the development of AI and machine learning as the largest cloud companies consolidate power.

Microsoft and OpenAI

OpenAI, the AI firm behind ChatGPT and image generator Dall-E 2, has received billions in investments from Microsoft. 

Part of the deal is for OpenAI’s Generative Pre-Trained Transformer 3 (GPT3) – a text generator AI software – to be integrated into Microsoft’s suite of products, and to open up this tech for other businesses. This AI integration is exclusively powered by Microsoft’s Azure cloud services.

Since the new infusion of funding, the ChatGPT train has not stopped. OpenAI immediately launched ChatGPT Plus in early February, charging $20 per month for new and priority features like faster response time even during peak times. This helped in research and data gathering – machine learning – to further explore the strengths and limitations of the technology.

Numerous upgrades were in place: ChatGPT is built into the Bing search, and Microsoft also introduced Microsoft Designer – which is a Powerpoint software enhanced with the capabilities of image generator Dall-E 2. 

Only a month after the partnership, OpenAI introduced an API that will allow any business to build ChatGPT tech into their apps, websites, products, and services. It hasn’t been a week since its release, and companies are already scurrying to get their hands on it and use it in their products and services. Some early adopters of ChatGPT API include Shopify, Instacart, and Salesforce’s Slack in the coming days.

In the much nearer future than expected – maybe even within months – AI chatbots will be common for enterprises, the productivity of white-collar workers will rise, and there will be an “AI goldrush” for OpenAI and Microsoft.

With usage over time, these chatbots through machine learning will significantly improve their responses, be trained on more recent datasets, and play a more crucial role in business operations – which can produce new sets of pros and cons in itself.

But one of the concerns moving forward is how this can potentially lead to more layoffs in order to accommodate the new technology – as exhibited by the massive layoffs in the tech industry.

As for Microsoft, the partnership with OpenAI is seen to benefit them greatly, as the tech giant is poised to take up a large share of the AI market. Not only this, but the company will also further integrate AI and machine learning across its office products and offerings.

Google’s Bard

Right after Microsoft joined forces with OpenAI, Google was scrambling to develop its own generative AI chatbot, eventually announcing Bard, which is still in beta testing with select “trusted users.” They expect to offer Bard to the public in the coming weeks.

Google is playing catch-up after weeks of OpenAI rollouts. The company has only divulged that Bard is not an AI for search, but is a collaborative and conversational AI service. The company said it will “create a suite of tools and APIs that will make it easy for others to build more innovative applications with AI,” much like what the Microsoft-OpenAI tandem did. 

Google Cloud also partnered with AI companies Cohere, C3.ai, and Anthropic to help these companies scale their AI systems. It is not clear, however, if these companies are helping Google in developing its AI offering.

Amazon’s AWS Partnership to Help AI Developers

AWS holds the majority share of the entire cloud market, at 34%. While Google and Microsoft race towards developing text generator AI applications trained on language learning models, AWS works more on the sidelines, empowering software developers in creating their AI applications.

It recently partnered with New York-based startup Hugging Face, working closely to create tools and services that will make it easier for developers to weave AI tech into their products and services and run it on the AWS cloud.

AWS’ cloud capabilities can make it possible for developers to use more computing power, which will allow them to reduce how much time it takes to create a chatbot or other AI products, and this can lead to money and time savings.

With AWS supporting AI developers, we can anticipate having faster and more rollouts of AI systems in the future, which can accelerate the pace of innovation and increase the level of quality for AI systems, applications, products, and services.

AI requires massive computing powers in the world to deliver solutions that can impact how we work in the future. Being able to supply the backbone on which AI is built, it is clear that the largest cloud service providers will have extensive control over the production of major AI applications, products, and services.

If current AI tools and services aid us in augmenting human creativity and decision-making, what more can they do in the near future when AI and machine learning blossom into fully developed and trained digital brains that can think and autonomously execute work like humans?

This blog post was originally published on the author’s blog and reprinted with permission.