As we enter 2023, artificial intelligence (AI) experts are making predictions about the direction the technology will take in the coming year. We have scoured the Internet for educated opinions on the matter, and we are surprised to learn some shocking revelations about the future of machine learning.
Many people find discoveries to be enigmatic in their early phases. More people will soon be aware of the wonders of artificial intelligence and the benefits it can bring to humanity. 2022 has been a year of many machine learning trials, and many projects have emerged with promising outcomes.
AI Predictions for 2023
Experts say AI will continue to transform industries and revolutionize our work. From healthcare to transportation to manufacturing, AI is changing how businesses operate and making them more efficient and effective.
TheNextWeb reports that Alexander Hagerup, co-founder, and CEO at Vic.ai, believes that we will see a shift towards humans relying on AI and machine learning software to do their work for them autonomously.
This will be particularly prominent in the creative industries, finance, and other back-office functions. Hagerup also thinks that a potential recession could accelerate this trend as businesses look for ways to reduce labor costs.
According to recent rumors, the next generation of OpenAI's powerful generative language model, GPT-4, is set to be released in the coming months. When GPT-4 comes out, it is expected to impact the field of artificial intelligence significantly and could be used in various industries and situations. Why? Because this new system is expected to be multi-modal.
The Good Things
According to a recent article by Datanami, AI will continue to be integrated into many industries and applications, focusing on improving efficiency, reducing costs, and enhancing decision-making.
Ethical AI teams will also continue to be an essential resource for companies, helping to ensure that AI outputs are aligned with values and executed in a reliable and trustworthy manner.
In addition, companies are expected to find new ways to use knowledge graphs for responsible AI, such as making ethical decisions more accurate, making them easier to explain, and reducing bias.
Running Out of Space?
A Forbes report tells us that the growing use of large language models (LLMs) in artificial intelligence (AI) raises concerns about the finite supply of high-quality text data available for training purposes. According to research, the world's total stock of such data may be between 4.6 trillion and 17.2 trillion tokens, including all books, scientific papers, news articles, Wikipedia, and publicly available code.
This article can explain or two about AI data tokens.
According to OpenAI's Sam Altman, the compute costs of ChatGPT are "eye-watering." At the same time, IBM claims they are running out of computing power entirely because AI models are "increasing exponentially," and the hardware to train and run them hasn't evolved as quickly. Meanwhile, according to one study, "data typically used for training language models may be used up in the near future-as early as 2026."
This means that the world may be approaching the limit of helpful language data for training LLMs, which could hinder further progress in language AI. To address this issue, researchers are looking for solutions such as synthetic data or transcribing spoken content from meetings to create additional language data. Developers will closely watch OpenAI's approach to its upcoming GPT-4 research to learn how this problem can be solved.
Overall, the future of AI in 2023 appears to be full of opportunities and potential, as well as some concerning challenges, and we can not wait to see what the year has in store.
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