What progress in AI looks like in 2024 – 2024-03-15 02:11:23

At an event in San Francisco in November, Sam Altman, CEO of artificial intelligence company OpenAI, was asked what surprises the field might have in store in 2024.

Los chatbots online like ChatGPT of OpenAI will have “a breakthrough that no one expected,” Altman immediately responded.

Sitting next to him, James Manyika, a Google executive, nodded and said, “I agree.”

This year’s AI sector is going to be defined by one main characteristic: an extraordinarily rapid improvement in technology as advances accumulate on top of each other, allowing AI to generate new types of media, imitate human reasoning of new ways and filter into the physical world through a new type of robots.

In the coming months, AI-based image generators such as GIVE HER and Midjourney, will instantly offer video and still images. And they will gradually merge with chatbots as ChatGPT.

This means that the chatbots They will go far beyond digital text, now they will handle photos, videos, diagrams, graphs and other media. Their behavior will increasingly resemble human reasoning and they will perform increasingly complex tasks in fields such as mathematics and science. As technology moves towards robots, it will also help solve problems beyond the digital world.

Many of these advances have already begun to emerge in the main research laboratories and in technological products. But in 2024, the power of these products begins to grow significantly and is used by many more people.

“The rapid progress of AI will continue,” said David Luan, CEO of Adept, an AI startup. “It is unavoidable”.

OpenAI, Google, and other tech companies are advancing AI much faster than other technologies because of the way the underlying systems are built.

Most software applications are created by engineers, one line of computer code at a time, a process that is often slow and tedious. Companies are improving AI more quickly because the technology is based on neural networks, mathematical systems that can learn skills by analyzing digital data. By detecting patterns in data such as Wikipedia articles, books, and digital texts pulled from the Internet, a neural network can learn to generate text on its own.

Below is a guide to how AI is changing this year, starting with shorter-term advances that will lead to further progress in its capabilities.

Instant Videos

Until now, AI-based applications primarily generated text and still images in response to instructions. For example, GIVE HER can create photorealistic images in seconds from requests like “a rhino diving off the Golden Gate Bridge.”

But this year, companies like OpenAI, Google, Meta, and New York-based Runway are likely to deploy image generators that also allow you to create videos. These companies have already created prototypes of tools capable of creating videos instantly from short text instructions.

Tech companies are likely to bring the powers of image and video generators to chatbots, making them more powerful.

Chatbots multimodales

Los chatbots and image generators, originally developed as separate tools, are gradually merging. Last year, when OpenAI introduced a new version of ChatGPT, the chatbot It could generate images as well as text.

AI companies are creating multimodal systems, meaning AI can handle multiple types of multimedia elements. These systems gain skills by analyzing photos, text, and potentially other types of media, such as diagrams, graphics, sounds, and videos, so they can then produce their own text, images, and sounds.

But that is not all. Because systems also learn the relationships between different types of media, they will be able to understand one type of media and respond with another. In other words, someone can enter an image into the chatbot and it will respond with text.

Better reasoning

When Altman talks about AI advancing, he is referring to the chatbots They are better at “reasoning” so they can take on more complex tasks, such as solving complicated mathematical problems and generating detailed computer programs.

The goal is to build systems capable of solving a problem logically and thoroughly through a series of discrete steps, each building on the next. This is how humans reason, at least in some cases.

Leading scientists disagree about whether chatbots can actually reason like this. Some argue that these systems only appear to reason when they repeat behaviors they have seen in Internet data. But OpenAI and others are building systems that can more reliably answer complex questions related to subjects such as mathematics, computer programming, physics and other sciences.

“As systems become more reliable, they will become more popular,” said Nick Frosst, a former Google researcher who runs Cohere, an AI company.

If chatbots reason better, they can become “AI agents.”

AI Agents

As companies teach AI systems to solve complex problems step by step, they can also improve the ability of chatbots to use software applications and websites on their behalf.

Researchers are transforming the chatbots into a new type of autonomous system called an AI agent. This means that the chatbots They may use software applications, websites, and other online tools, such as spreadsheets, online calendars, and travel sites. In this way, people could delegate to chatbots tedious office work. But these agents could also take away jobs entirely.

Chatbots already act as agents on a small scale. They can schedule meetings, edit files, analyze data, and create bar charts. But these tools don’t always work as well as they should. Agents break down completely when applied to more complex tasks.

This year, AI companies are set to introduce more reliable agents. “You should be able to delegate any tedious day-to-day IT work to an agent,” Luan said.

This could include tracking expenses in an app like QuickBooks or recording vacation days in an application like Workday. In the long term, it will extend beyond software and internet services and into the world of robotics.

Smarter robots

In the past, robots were programmed to perform the same task over and over again, such as picking up boxes that are always the same size and shape. But with the same type of technology that chatbots rely on, researchers are giving robots the ability to perform more complex tasks, including ones they have never seen before.

Just as chatbots can learn to predict the next word in a sentence by analyzing large amounts of digital text, a robot can learn to predict what will happen in the physical world by analyzing countless videos of objects being poked, lifted, and moved.

This year, AI will power robots that operate behind the scenes, like the mechanical arms that fold shirts in a laundromat or sort through piles of stuff in a warehouse. Technology titans like Elon Musk are also working to introduce humanoid robots into homes.


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