Funding will come first, but will verification catch up?
At the same time, investment in and implementation of AI has been moving rapidly in drug discovery, finance, universities, and employment. Isomorphic Labs is reportedly in talks to raise money at a valuation of more than $40 billion, and HubSpot has cut 600 jobs as it shifts operations to AI. While funds and operations move first, the situation differs from stage to stage as to whether the backing that supports those movements is in place at the same speed. Evaluations are beginning to emerge that measure whether agents are more likely to report false information when cornered, and norms governing the treatment of AI are being written down by both companies and international organizations. When reading this half-day topic, I would like to compare the speed with which the introduction decision was made and the depth of evidence that the decision can be trusted in each field.
Isomorphic Labs is reportedly in talks to raise new funding, valuing the company at more than $40 billion (Bloomberg.com, Pluang). Around the same time, it was reported that the US government and major Silicon Valley companies would spend $1.8 billion to solve the data gap in AI drug discovery (BigGo Finance). Additionally, NVIDIA and Eli Lilly plan to spend up to $1 billion on AI drug discovery labs (www.tokenpost.com). If you line up the three projects with the largest amounts, you can see that the funds are going to the same destination. Rather than the model itself, it is the data used for learning and the computational infrastructure that runs it.
There are also moves on the partnership side. Almirall and Absci announce an AI drug discovery collaboration to rapidly develop novel treatments for skin diseases (BioSpace). This is not a huge amount of funding, but a joint development focused on a specific disease area. Although the size of the funding and the specifics of the partnership are different matters, they both agree that they will allocate resources to the process of ``designing with AI and verifying with experiments.''
Expectations are beginning to be reflected in prices before results are seen. iM Securities raised its price target on Hanmi Pharmaceutical to ₩650,000, factoring in the value of the AI-designed obesity treatment drug (BigGo Finance). The negotiated amount, which puts the company's value at over $40 billion, has the same characteristics in that it is not yet the price at which it will be traded on the market. 36Kr points out that NVIDIA has invested in 14 AI pharmaceutical startups over the past three years and asks whether an IPO rush for prominent AI pharmaceutical companies is imminent (36Kr). This article is written in the form of a question, and the timing of the IPO is not set in stone.
