What I Read This Week...
Salesforce stock drops more than 20% after releasing Q2 earnings, investor sentiment is shifting on generative AI, and a new drug offers the possibility of tooth regeneration in humans
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Caught My Eye…
Salesforce’s share price dropped more than 20% after releasing its Q2 2024 earnings, despite earnings falling just 0.3% below Wall Street analysts' expectations. What's going on? Two factors appear to be responsible for this decline. First, a slowing economy poses a risk to revenues as customers more carefully evaluate the return on investment of Salesforce’s products before committing to a purchase. Second, analysts are concerned that generative AI could help competitors deliver similar functionalities to Salesforce at much lower costs, which could erode the company’s margins over time.
The AI revolution is already losing steam as investors are becoming more cautious about generative AI, recognizing that the current spending doesn't match its near-term potential to drive returns. Why is this happening? The pace of improvements in large language models is slowing as companies exhaust all the available data on the entire Internet, resulting in models and applications becoming commoditized over time. Moreover, while chatbots serve as useful assistants, they still struggle to replace the specialized knowledge of human experts, leading to a more tempered outlook on the mass adoption of AI applications and their near-term profitability.
A new study by Kyoto University and the University of Fukui has discovered that an antibody for the gene USAG-1 can stimulate tooth growth in mice and ferrets, offering hope for adult humans with tooth loss. How does this work? The study found that targeting the gene USAG-1 with a specific antibody can stimulate tooth growth by interacting with BMP signaling, a pathway in the brain that is involved in the differentiation and growth of dental tissues, including teeth. A drug with this antibody will undergo its first human trial in September.
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Outside of investor sentiment, the actual utility of LLM's is also losing its shine. Trying to find some use of AI in equity research. Looking for the intersection of 3 Venn diagrams: The quality of the prompts / The quality of the LLM / The quality of the data. It's the last one that is lacking. I've tried uploading all annual reports and documents of a specific company to get a "company Chatbot" to talk to, but the results are mixed.