In 2023, the most significant IT trend became AI and neural networks, specifically a particular type of these neural networks—Large Language Models (LLMs), which have greatly influenced the industry. This is evident by the amount of investment currently flowing into companies that apply artificial intelligence in some form, especially those utilizing Large Language Models. This article discusses the main changes in the technology sector and what to expect in the coming years.
AI Startups as a Profitable Area for Investors
As an investor and limited partner in the venture fund Davidovs Venture Collective (DVC), I can say that we invest in such companies at early stages. Over the past year and a half, we have invested in a number of companies related to artificial intelligence. This includes 63 startups, 75% of which are based on AI technologies. Specifically, this year, about 90% of the companies we invested in are somehow connected with neural networks.
Now, most IT companies that were previously not associated with AI, or did not particularly emphasize it, have rushed to apply AI in their systems. Large companies are acquiring small AI startups to integrate them into their business. And this is no accident.
Changes Illustrated by Major Companies
What is happening now is a so-called market disruption, where new technology completely changes the landscape of businesses in this area. For example, Adobe, the creator of Photoshop, Adobe Premiere, and other media content services, is now actively applying AI.
Another example is Notion, which has already implemented artificial intelligence in creating notes and knowledge bases. Thus, AI is a significant trend that both newcomers and larger players in the market are striving towards. AI has gained widespread recognition this year, but in reality, it has been used in software products for quite some time. This year has become the year of Large Language Models. And tasks that were previously unsolvable are now being addressed with the help of Large Language Models, which is also a kind of revolution.
The Main Breakthrough of Neural Networks
However, what began to happen next was perhaps even more surprising. Neural networks have become very effective in classification tasks, such as image recognition. This was one of the biggest breakthroughs this year. When OpenAI added the feature to ChatGPT: you can upload any image, and it will describe what is depicted in the photo.
Neural Networks and Robotics
Thanks to this, a significant revolution is now taking place in robotics. Previously, specific neural networks, which needed to be extensively trained to recognize a multitude of different objects, were required. For a robot to recognize basic objects like a table, chair, glass, bottle, etc., the neural network had to be trained for each of these objects, and the training process was quite lengthy. Additionally, for a robot to navigate in space, complex algorithms for recognizing these images were again needed.
On the Example
With the advent of Large Language Models, it has become possible to simply describe any algorithm. You can literally give a robot a task like “go to the kitchen and bring me a bottle of cold water”. Thanks to it operating on a Large Language Model, it doesn’t even need to be explained what exactly it needs to do. It understands from the context that the water is likely in the refrigerator.
Before the advent of Large Language Models, we would have had to give it a very precise instruction: get to the kitchen, open the refrigerator, take out the water, close the refrigerator, and so on. All this had to be included in the instruction. But now, none of this is necessary thanks to the advent of Large Language Models. And if the robot opens the refrigerator and doesn’t find water there, it can even search the cabinets. These advanced neural networks understand details from the context and independently construct a logical chain.
What Will Change?
All of this affects the world of IT in such a way:
- Firstly, everyone wants to invest in AI,
- Secondly, all companies are trying to quickly apply AI in their developments, because otherwise, they will be displaced from the market by new and more agile companies.
The same Adobe, Microsoft, Google, and so on, invest a lot in AI startups and buy them at high rates. It results in a third component: within the AI field, there’s a redistribution of spheres of influence. That is, other neural networks that operate on different principles are being displaced by Large Language Models.
For example, the classic field of computer vision, which was used for robotics and image recognition, has become somewhat unnecessary. Because expertise becomes useless thanks to the application of the new technology of Large Language Models.
If the term AI is now widely used, previously neural networks were called machine learning. In a few days, I will have a meeting with someone who has been working in this field for several years. He has faced a problem, as he works with other types of neural networks. And he has concerns related to becoming unnecessary with the progress of Large Language Models.
The Second Trend: based on Large Language Models, autonomous agents or autonomous AI employees will be actively developed. This is a significant direction, where we no longer consider an AI service as a tool, but as a digital employee. When you hire a virtual designer and formulate your request to him. He delivers a finished result: for example, a website design. You will communicate with him as with a person—such interactive mode.
This is a very big direction up to the point that complete automation of managers is possible. What people are currently working on. In the field of AI—these are virtual managers who will monitor performance, employee parameters, and manage the team. All this will happen in the coming years.
I would keep an eye on the largest companies in this area. These are OpenAI, Ethrophic, Google Bard, and all the large LLMs that we currently have. We continue to wait for the biggest breakthroughs in the field of Large Language Models. They are constantly becoming more complex, larger, and more sophisticated.
