Scientists fighting a robot
On February 19, Google announced their co-scientist platform of the one that begins with a search purpose and then uses seven agents:
- a generation agent,
- reflection agent,
- rank agent,
- agent of proximity,
- Meta review agent,
- evolution agent and a
- The supervisor agent who oversees the entire effort.
In short, every scientist now has a staff of seven digital workers to help them with everything, from the idea to the discovery. It is not only the extra work that is exciting, but they have included a “self-play” approach in which different ideas between agents are debated. Evolves its ideas while playing through different options and examines their severity and facts available to the hypothesis.
Excellent early performance by he agents
When the AI-CO’s ideas were revised by true scientists in their field, it was almost equally valued in the possible impact of their ideas, as well as strong innovations. For example, it comes out with the new candidates repurpoing drugs for acute myeloid leukemia (AML) which were then clinically tested and proved to be clinically important. There were also strong results regarding the mechanism of antimicrobial resistance, and the causes of liver fibrosis.
Great implications for many businesses
For many businesses an improvement in science has tremendous implications. For example, one of the critical things Spacex did was to push the limits of aluminum welding methods so that they can reduce the cost of building a rocket pipe. The Spacex method needed fewer panels raised, but still had high strength and low weight – all at a lower cost. Everyone manufacturer often benefits from scientific progress.
Likewise, firms, such as pharmaceutical firms, or energy companies, or computer organizations can benefit greatly from faster, more accurate and perhaps less expensive science. I remember an old quote told by the late Gordon Bell talking about something Bob Noyce, the founder of Intel once said in a board meeting: “Remember scientists create all value, you guys in marketing and finance just push it around . ”
The other important thing to remember is that these large linguistic models are built on the matrix matrix, which allows very different types of data – images, words, sensor readings, etc., for everyone to live in a common space of knowledge while being analyzed. I am optimistic that this cross data, the analysis of the cross context will provide new knowledge and dramatic findings. We are only at the beginning.
Here Three practical actions A leader must take in mind the young Google Co-scientist Tool:
1. Set up an Augmented R&D strategy Ai-
🔹 Why? The co-extension of it accelerates the generation of hypotheses and research planning, reducing time into scientific advances.
🔹 The action:
• create a The internal search laboratory of he OR University partner To pilot his co-scientist.
• lever he in Expand in the scientific fields adjacent where your company has expertise, but lacks depth.
2. Create an AI-scientist-in-the-Loop culture
🔹 Why? He does not replace human expertise, but increases it. Company Integrate it into their research teams Will exceed competitors.
🔹 The action:
• train scientists and engineers to work with him as co -workernot just tools.
• develop Research Streams of Research “The First” where the teams prove and refine the hypotheses created by him before they perform resources.
• encourage one scanallowing him to Challenge the traditional R&D assumptions And explore iododox solutions.
3. Employ the scientific talent working with/or build new models
🔹 Why? Scientists who learn how to use and build these tools will create value for all their colleagues.
🔹 The action:
• Work with training academic institutions scientists and engineers to work with him.
• develop Internal learning laboratories to share and increase internal expertise.
• give Small grants for academic institutions who specialize in those fields of science that interest your firm.
The speed of science is increasing: don’t lose the race
Remember that all your assumptions about the speed of scientific discovery can be real obstacles to your detection process. Large language agents and patterns change the generation and liquidity of knowledge radically. Most importantly, remember that google-based scientists never get tired, never sleep and can always explore and improve every hour of every day of each year.