This article has been machine-translated into English. Therefore, there may be nuances or errors in the content. The Danish version is always up-to-date and accurate. Read the original Danish article here.
Over the past week we took a short winter break, so there was no Monday newsletter. But we’re back now, and here we’ve gathered all the latest on artificial intelligence and education.
The past week has been a race between the major players in artificial intelligence, with several new products launched. Google unveiled its Gemini 1.5 Pro, which can handle a great deal of content, and OpenAI explained how they are working to build memory into ChatGPT. But the really big news has probably been that OpenAI has just launched a text-to-video model that, in many ways, raises the bar for what is possible. In this newsletter we put on our teaching hat and offer our own prediction of what it could mean for the learning materials of the future.
In addition, Denmark also introduced a new digitalisation strategy, and we have extracted the key points that concern the education sector.
Happy reading
OpenAI's Sora: Text to video
Last week, OpenAI unveiled its text-to-video model, called Sora. What sets Sora apart from systems such as Runway and Pika is its very high quality and the ability to generate videos of up to a minute. If you haven’t seen the videos, OpenAI has collected the most interesting ones here:
The model can also create multiple videos of the same situation from different angles:
Looking a little more closely at the videos, you’ll notice that they are of incredibly high photorealistic quality, and that people and objects in the background follow the camera’s movements. Sora appears to develop a strong 3D “understanding” of scenes, with characters and objects moving realistically in a continuous manner. If you’re interested in how Sora works, we recommend reading Mike Young’s article: How Sora (actually) works.
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Sora in the classroom In future, the technology could be used in teaching to enrich learning resources. For example, Sora can be used to generate videos that visualise historical events or explain scientific concepts in ways that may enhance pupils’ understanding (provided, of course, that rigorous source criticism is applied). And if the pupil or teacher can describe the content, Sora will be able to visualise the ideas and thus unfold the content in an engaging way, tailored to the individual pupil.
At Viden.AI, we envisage that, over time, teaching materials will evolve into advanced multimodal, interactive and adaptive learning resources, tailored to the individual, where pupils themselves initiate their own learning experiences.
On 8 February 2024, Denmark adopted a new digitalisation strategy, with the government allocating 740 million kroner for investments in digitalisation. Below, we have gathered the key initiatives concerning the education sector.
160 million kroner are allocated in 2024–2026 to integrate technological understanding into teaching in the Danish primary and lower secondary school (folkeskole).
10 million kroner are invested with a focus on further development of teacher education. This also includes professional development for educators.
35 million kroner are allocated in 2024 for the development of digital competences and teaching in higher education.
30 million kroner are invested in 2024–2026 in continuing education and retention of IT specialists, and in strengthening part-time industry master’s pathways (erhvervskandidatforløb) in IT degree programmes.
61 million kroner are allocated to strategic initiatives for the use of artificial intelligence in the period 2024–2027, including the potential development of a Danish language model.
Google Gemini stores your conversations for up to three years
What you write to Google Gemini may be reviewed by humans and used to improve the model, and these data may be stored for up to three years.
Conversations that have been reviewed or annotated by human reviewers (and related data like your language, device type, location info, or feedback) are not deleted when you delete your Gemini Apps activity because they are kept separately and are not connected to your Google Account. Instead, they are retained for up to three years.
More generally, users should be very mindful of how they use language models. For example, ChatGPT stores conversations for 30 days, unless the user has an enterprise-level subscription.
OpenAI is rolling out a new feature for ChatGPT that lets the language model draw on information from earlier conversations, or you can have it remember something specific. For example, when designing teaching sequences, it can be useful for ChatGPT to know in advance that each module is 105 minutes, and also how you prefer everything to be set up.
The feature has been rolled out to a small group of users and will later be rolled out to a wider group.
The new version of Gemini, called 1.5 Pro, can handle very large amounts of content in context, up to 1 million tokens (10 million tokens for research). This means the language model can find specific information in very large datasets. One example is a video analysis of Buster Keaton’s film “Sherlock Jr.”, where the model scanned every single frame and converted them into tokens. It was then possible to search the film for specific information. Watch the video below:
This article by Josh Bersin looks at the potential of autonomous learning platforms for companies, powered by artificial intelligence. The aim is to make knowledge management personal and a compelling user experience, making it engaging for employees to pursue further training. By using artificial intelligence, it becomes possible to make a company’s content dynamic and to create tailored courses that include videos and simulations.
This could mean a significant change in how companies upskill their employees.