2023 Artificial Intelligence Predictions

As businesses prepare to welcome the year 2023, strategists have already reflected their expectations for the new year in their planning based on their predictions and analysis reports. According to forecasts, 2023 will be the year of investments far exceeding the investments made in technology so far. Artificial intelligence platforms are planning to increase their investments and venture funds. For this reason, companies will restructure their artificial intelligence strategies and expand their corporate expansions. According to Forrester’s research report, in 2023, global markets and businesses of all sizes will be transformed by artificial intelligence. In other words, the silent revolution of digital transformation will accelerate.

In the last few years, there have been exciting developments in artificial intelligence, and what used to be imagined as science fiction has become a daily component of our lives with artificial intelligence. Artificial intelligence technology will continue to witness significant developments in terms of imitating human skills and behaviors such as reasoning, perception, perception, comprehension, judgement, planning and communication through the development of various software and data algorithms. 2023 studies will be impressive for artificial intelligence studies that are more humanoid, more effective, efficient in the field of business and equipped with the ability to interpret much larger data. What do you think, will the year 2023 of corporate life introduce us to our humanoid colleagues? Although the answer to this question is not yet known, the main predictions of experts are as follows:

1-) Systems that can interpret higher data and more complex algorithms at a lower cost are expected to be established.

According to IT experts, in the new year, artificial intelligence companies will introduce their new models, which have been worked on for a long time, to the market and start working on the next models. In particular, it is stated that artificial intelligence models that can work on larger datasets with fewer parameters for optimum model performance will be studied and the next models will be developed in this direction.

2-) OpenAI’s powerful and productive language model, which is expected to appear on the stage in the next few months: GPT-4 is expected to be introduced and make a big impact.

At this point, according to experts, it is stated that the difference of this model, which will be newly released to the market, from its predecessor may be that it can interpret larger data sizes.

3-) Turing Bots are expected to develop enough to write 10 per cent of the code and tests worldwide.

The evolutionary development of Turing Bots, artificial intelligence models that can write code, has progressed considerably since the Turing test. Today, it is estimated that the integration of Turing Bots, on which work continues with a focus on language models and learning, will increase and reach the capacity to solve one tenth of the codes and tests worldwide in 2023.

4-) Ten per cent of Fortune 500 companies are expected to produce content with artificial intelligence tools.

The question of how possible it is for artificial intelligence to create meaningful content has been driving artificial intelligence studies in recent years. Therefore, investments in this subject will continue to increase and developments on the subject will continue to be recorded. It is stated that at least 10 per cent of investments are expected to be allocated to the creation of artificial intelligence-supported digital content by at least 10 per cent of companies. Models in which complex algorithms will transform elements such as text, images, visuals, and sound into content are expected to be used in business life.

With Generative AI, according to Gartner, it is estimated that 30% of outgoing messages from large organizations will be synthetically generated by 2025.

5-) Data problems are expected in artificial intelligence language models.

According to Forbes, data in language models is limited and at risk of exhaustion. Forbes explains this argument with the results of research efforts such as DeepMind’s “Chinchilla” study. According to these results, “the most effective way to build more powerful large language models (LLMs) is not to make them bigger, but to train them on more data”. In other words, it explains the concern that there is insufficient language data in the world and that the texts on the internet will not yet be enough to train an artificial intelligence language model.

6-) One in four technology executives is expected to be able to report to boards of directors on AI management.

It is stated that 46% of the managements or boards that make decisions based on data and analytical reports in the business world are looking for artificial intelligence support in artificial intelligence applications. Considering that there are no human errors, complex algorithms of big data are transformed into comments in a short time and contribute to decision-making, it can be stated that this has become a natural need.

7-) The development of artificial intelligence modelling and increasing the operational benefits and costly developments are expected to be used only by certain companies in the first place.

Important steps are expected to ensure productive artificial intelligence, advanced coding and smoother artificial intelligence operations. While it is stated that artificial intelligence models can become quite complex with millions of parameters, the ability to work on multiple experiments at the same time can increase exponentially, it is stated that this requires a cost-effective computing system for its functionality, so memory-intensive studies may be the subject of the following years. Only around a quarter of companies have AI systems in widespread production, and only a limited number of organizations are expected to see the enterprise-class AI cloud service of 2023 emerge next year to address this challenge and capture a huge market opportunity.

8 -) Driverless vehicles are expected to be used.

It was announced that contrary to popular belief, this technology is ready and will be used in transport in 2023, and even “robo-taxis” will be on display.

9-) Artificial intelligence platforms (except Midjourney) will increase their investments by outsourcing.

According to Forbes: Midjourney is the only organisation that does not accept external funding, capital and support, while OpenAI and Stability AI are increasing their capital by collecting investments from external sources.

10-) The classical way of searching for information from search engines is expected to disappear.

In 2023, it is stated that the popular search format that Google has gained over the last 20 years will be out of our habits. The way of accessing digital information will change. Today’s large language models are literate at a highly complex level, but are expected to change the way we do things.

It remains to be seen whether the increase in speech/dialogue searches will, over time, overcome the data problem mentioned in point 5 and pave the way for new developments. Considering that dialogue-based search will become popular, this benefit seems quite possible.

11-) Efforts to develop humanoid robots are expected to attract significant interest, funding and talent, and several new humanoid robot initiatives are expected to be launched.

The development history of humanoid robots dates back to quite a few years. While the development of humanoid robots continues rapidly, it is not far away that they will enter our daily lives, workplaces and shopping areas.

12-) The concept of “LLMOps” is expected to emerge as a new version of MLOps.

In recent years, with the huge investments in machine learning tools, commonly referred to as MLOps, it is stated that the subject will be further developed and will trigger interesting developments in the coming year.

13-) The number of research projects building on or citing AlphaFold is expected to increase.

DeepMind’s AlphaFold platform has solved one of the greatest mysteries of life: and while it is stated that this is the “protein folding problem”, the AlphaFold discovery in this field is expected to shed light on this problem and is a landmark achievement and can trigger important discoveries. According to Forbes, AlphaFold represents the most important achievement in the history of artificial intelligence, and this innovation, which is a “vast new treasure trove of basic biological knowledge”, will be used to produce world-changing applications across disciplines, from new vaccines to new types of plastics.

14-) Billions of dollars of new investment commitments are expected to be announced to build chip manufacturing facilities in the US.

After the recent crisis in chips, which are an important power provider of artificial intelligence hardware, the market is expected to mobilise this year. In 2023, the US government is expected to take action to produce chips produced in China and Taiwan in advanced chip manufacturing facilities on its own soil.