AI on holiday: avatars, deepfakes and travel tech (the future is here) | Newsy AI

The following entry supplements the sixth episode of our Beyond AI podcast. In addition to the descriptions below, you can learn many more things about the latest developments in the world of AI from Michał and Ziemek's conversation. Enjoy!

Artificial intelligence (AI) and language models such as LLM (Large Language Models) are rapidly developing technologies that are becoming increasingly important in today's world. In this article, we will look at how these models work, how the data they are trained on affects their capabilities, and what challenges and threats the development of this technology poses.

Language models and user personalities

Contemporary language models, such as GPT-4o, are not only capable of generating text, but also of analyzing communication and drawing conclusions about users' personalities. This is possible thanks to advanced algorithms that can interpret the style of speech and its context. With the right “prompting,” or commands, these models can generate descriptions of personality traits based on text analysis.

Such applications may prove useful not only in everyday communication, but also in more advanced areas such as psychology and marketing. Language models that analyze speech style can help to better understand customer preferences and needs, opening up new opportunities for service personalization.

Model comparison: Chat GPT vs. Claude

In discussions about language models, different solutions are often compared, e.g., Chat GPT and Claude. It is worth noting that these models differ in terms of language generation quality, especially in the context of languages other than English. Claude, although it has many advantages, tends to anglicize when generating Polish text. Chat GPT, on the other hand, handles Polish better, which may be due to its ability to “learn” from the history of conversations with the user, i.e., its “memory” function. Thanks to this, the model adapts its responses to the user's style, which improves the quality of the generated content.

Small language models and their advantages

In addition to large models such as GPT-3 and GPT-4, smaller language models such as Ministral 3B and 8B are also being developed. These are compact solutions that can be run locally on users' devices without the need to send data to external servers.

The main advantage of these small models is that they protect user privacy, as they do not require information to be sent to third parties. In addition, these models perform well in generating text in Polish, which makes them an interesting alternative to large, external solutions.

The practical application of language models

Language models are finding increasingly wider application in various areas of life. One of the most interesting examples is Rufus, a shopping assistant developed by Amazon. Rufus helps customers choose products by offering advice based on technical specifications and other users' reviews.

Another example of the practical application of LLMs is the chatbot on wakacje.pl. This virtual advisor can provide information about hotels, weather, and tourist reviews, helping users choose the perfect vacation.

Interactive avatars – a new way to communicate

Modern technologies such as AI also offer new possibilities in communication, including interactive avatars. Zoom plans to introduce avatars that can replace users during online meetings. Another company, HeyGen, creates avatars that can translate speech into other languages while synchronizing lip movements with sound. What's more, HeyGen is also developing a feature for interactive avatars that will act as chatbots, pretending to be the user and answering questions.

Deepfakes and legal challenges

One of the challenges associated with the development of artificial intelligence is deepfakes, i.e., technologies that allow the creation of realistic but fake images or videos. An example is the Kamala Harris deepfake, which became part of the US election campaign. Similar technologies are used not only in politics but also in entertainment, such as the parody created by Elon Musk.

Although some of these examples are relatively harmless, deepfakes can also be a tool for manipulation. For example, a deepfake of President Zelensky was used in a disinformation campaign in Russia. As a result, many countries, such as California, are trying to introduce legal regulations on political deepfakes. However, issues related to freedom of speech make it difficult to enforce such regulations.

Research on language model reasoning

Another interesting aspect of artificial intelligence is research into the logical reasoning abilities of LLMs. Research conducted by Apple, Microsoft, and DeepMind has shown that these models have difficulty performing tasks that require reasoning, especially when the tasks are modified. These models rely primarily on pattern recognition rather than a true understanding of the problem.

It is also worth noting that open-source models, such as GPT-3, are more susceptible to a decline in quality when elements unrelated to the topic are added to the task. These problems also affect other models, such as GPT “o one preview.”

The importance of prompts in AI content generation

A key element of working with language models is proper “prompting.” Research shows that the precision and conciseness of a prompt have a huge impact on the quality of the AI-generated response. Experimenting with different prompts and iteratively improving them allows for more accurate and consistent responses. It is also important to provide full context in commands, which is similar to the principles of effective interpersonal communication.

Risks associated with the development of artificial intelligence

The Doomsday Clock, a well-known symbol warning of global threats, has in recent years also pointed to the risks associated with the uncontrolled development of artificial intelligence. Automation and self-improving AI systems raise concerns in terms of security and ethics.

Alongside the potential threats of nuclear war and climate change, AI is becoming another key factor that could have a decisive impact on the future of humanity.

FAQ – artificial intelligence and language models

1. How do language models work?

Language models such as GPT-3 are trained on huge text datasets, enabling them to generate answers to questions, write articles, and even hold conversations.

2. What is a deepfake?

Deepfake is a technology that allows the creation of realistic but fake images, videos, or audio recordings that can be used for manipulation.

3. What are the advantages of small language models?

Small language models, such as Ministral 3B, run locally on users' devices, providing greater privacy and eliminating the need to send data to external servers.

Glossary

• ‍AI (artificial intelligence) – a field of technology concerned with creating systems capable of performing tasks that require human intelligence
• ‍LLM (Large Language Model) – a large language model that generates texts based on training data
• ‍Promptowanie – the process of giving commands to AI in order to obtain the appropriate response
• ‍Deepfake – technology that generates realistic but fake images or videos

We invite you to visit the Beyond AI channel, where you will find more content on the dynamic world of artificial intelligence. The channel's motto is “Your guide to the dynamic world of AI.”