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Light is all around us, essential for one of our primary senses (sight) as well as life on Earth itself. It underpins many technologies that affect our daily lives, including energy harvesting with solar cells, light-emitting-diode (LED) displays and telecommunications through fiber optic networks.

The smartphone is a great example of the power of light. Inside the box, its electronic functionality works because of quantum mechanics. The front screen is an entirely photonic device: liquid crystals controlling light. The back too: white light-emitting diodes for a flash, and lenses to capture images.

We use the word photonics, and sometimes optics, to capture the harnessing of light for and technologies. Their importance in is celebrated every year on 16 May with the International Day of Light.

Lately, there have been many headlines about scientific fraud and journal article retractions. If this trend continues, it represents a serious threat to public trust in science.

One way to tackle this problem—and ensure public trust in science remains high—may be to slow it down. We sometimes refer to this philosophy as “slow science.” Akin to the slow food movement, slow science prioritizes quality over speed and seeks to buck incentive structures that promote mass production.

Slow science may not represent an obvious way to improve science because we often equate science with progress, and slowing down progress does not sound very appealing. However, progress is not just about speed, but about basing important societal decisions on strong scientific foundations. And this takes time.

Today, we’re launching Anthropic’s AI for Science program – a new initiative designed to accelerate scientific research and discovery through access to our API. This program will provide free API credits to support researchers working on high-impact scientific projects, with a particular focus on biology and life sciences applications.

Why AI for Science? At Anthropic, we believe that AI has the potential to significantly accelerate scientific progress. Advanced AI reasoning and language capabilities can help researchers analyze complex scientific data, generate hypotheses, design experiments, and communicate findings more effectively. By reducing the time and resources needed for scientific discovery, we can help address some of humanity’s most pressing challenges.


Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems.

Our research found that the phenomenon arises when the part of the brain which detects familiarity de-synchronises with reality. Déjà vu is the signal which alerts you to this weirdness: it is a type of “fact checking” for the memory system.

But repetition can do something even more uncanny and unusual. The opposite of déjà vu is “jamais vu”, when something you know to be familiar feels unreal or novel in some way. In our recent research, which has just won an Ig Nobel award for literature, we investigated the mechanism behind the phenomenon.

Jamais vu may involve looking at a familiar face and finding it suddenly unusual or unknown. Musicians have it momentarily – losing their way in a very familiar passage of music. You may have had it going to a familiar place and becoming disorientated or seeing it with “new eyes”