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Home»AI»Key AI developments in 2023 and what to expect in 2024
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Key AI developments in 2023 and what to expect in 2024

5gantennas.orgBy 5gantennas.orgFebruary 1, 2024No Comments4 Mins Read
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Google Vision performs facial recognition on a photo of a man with facial features identified and a facial bounding box, San Ramon, CA, November 22, 2019. (Photo credit: Smith Collection/Gado/Getty Images)

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2023 will be a year filled with AI, and sometimes dozens of new developments will be announced in a single day. How can we tell what will really matter in the coming decades? Here are three things I think will really matter for 2024 and beyond.

Flywheel

For many people new to the field, the pace of new AI adoption can be incredible. But there is a reason for this pace. The flywheel, which was installed many years ago, is turning faster every day. What caused the AI ​​flywheel? It was a perfect storm of three developments

  • Ubiquitous computing. Cloud services have made significant computing power available to anyone with an email address, making it easy to build and create new AI. Even laptop computers can be used to build powerful AI, and smartphones can perform AI predictions for everything from facial recognition to avatar interaction.
  • Open Source. Open source software didn’t start with AI, but much AI development is open sourced (meaning anyone can try out and build on new AI techniques).
  • Data is everywhere. There are large public datasets that can be run on available computing using open source code.

What does this mean? This means that every time a new AI development is announced, a better version will soon follow and further improvements will be made. The flywheel rotates faster and faster.

AI literacy

AI literacy, or a general and broad understanding of AI across all aspects of human life, was being developed before 2023. However, with the advent of ChatGPT and similar tools, awareness of AI has become mainstream. AI literacy has gone from being a nice-to-have to a necessity. 2023 was the year the world realized that AI education is a must for everyone.

AI regulation and risks

Pervasive AI comes with risks, everything from misinformation to AI-related privacy risks, failures, and mistakes. 2023 saw an increase in regulatory flow, from the US AI Bill of Rights to the European Union’s evolution of AI legislation. Examples of AI risks are increasing every day, further recognizing the need for regulation and oversight.

What will happen in 2024?

All three of these areas will experience dramatic growth in 2023, and their growth will feed into each other. So all three will continue to be big trends in 2024. In the coming weeks, we’ll use this article to predict what major AI developments will be in 2024.

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I’m an entrepreneur and technologist in the AI ​​space, and I’m the founder of AIClub and AIClubPro (https://corp.aiclub.world and https: I am the CEO of //aiclubpro.world). I am also the author of Fundamentals of Artificial Intelligence, his first AI textbook for middle school and high school students.

Previously, I co-founded ParallelM and defined MLOps (Production Machine Learning and Deep Learning). MLOps is a practice for complete lifecycle management of machine learning and AI in production. My background is in software development for distributed systems, with a focus on machine learning, analytics, storage, I/O, file systems, and persistent memory. Prior to becoming PM, he was a lead architect/fellow at Fusion-io (acquired by SanDisk), where he developed new technologies and software stacks for persistent memory, non-volatile memory file systems (NVMFS), and application acceleration. was doing. Prior to Fusion-io, he was the technology lead for server flash at Intel, where he led non-volatile memory technology development and partnerships for server platforms and foundational work on NVM Express.

Prior to that, he was Chief Technology Officer at Gear6, where he built clustered compute caches for high-performance I/O environments. I completed my PhD at the University of California, Berkeley, researching clusters and distributed storage. I hold his 63 patents in distributed systems, networking, storage, performance, key-value stores, persistent memory, and memory hierarchy optimization. I enjoy speaking at industry and academic conferences and serving on conference program committees. I am currently co-chairing USENIX OpML 2019, the first industry conference on operational machine learning. I also serve on the steering committees for both OpML and HotStorage.

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