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Biology has Forever Changed
Plus: a prompt to save you hours every week
Hello Tensor Black Fans!
Biology has forever changed and OpenAI wants to be Google, with a fresh new search bar on the eve of Google I/O. Never a dull moment!
We’re still digesting the news from DeepMind’s incredible AlphaFold3 modeI, which can imagine the shapes of most biological molecules and how they interact. AlphaFold has done the work of one billion PhD years of work, and its available for research today.
Read on and Level Up:
AlphaFold 3 Revealed
Pharmacy AI Revolution
AI Chatbots Mystify Again!
GenAI Leads AI Deployments
AI’s Risky Scientific Shortcut
The Agents are Coming
Have a great week,
The TensorBlack Team
No time to read? Use AI to summarize the key findings of a research paper and how it might affect your practice. Here’s an example.
Download the PDF
Login to ChatGPT (you’ll need the Pro subscription)
Toggle the model to GPT4, not GPT3 (a dropdown menu)
Click the paper clip icon to upload your paper.
Enter the prompt below.
Hit Enter
I have attached a new research paper related to oncology. Please analyze it and provide a quick summary in three crisp, impactful, punchy and memorable sentences that highlight key findings or messages. Focus on aspects that could positively impact my practice as an oncologist. Ensure the language is plain and suitable for a 10th-grade reading level.
What’s Hot
Deepmind’s AlphaFold 3 accurately predicts the structures and interactions of all biomolecules, revolutionizing drug discovery and biological research.
Details
The animation shows AlphaFold 3 predicting how a molecule binds to DNA, where the prediction is in blue and purple, the known truth is in gray.
AlphaFold 3 improves interaction prediction accuracy by at least 50%, with some interactions seeing a doubling in accuracy.
The model extends beyond proteins to DNA, RNA, and ligands, enhancing our understanding of cellular processes and disease mechanisms.
Available for free via AlphaFold Server, this tool allows global researchers to access cutting-edge AI predictions to accelerate scientific innovation.
Why It Matters
AlphaFold 3's enhanced accuracy in predicting biomolecular structures and interactions could speed up oncology research, leading to faster and more effective treatment innovations. This advancement supports oncologists and caregivers by potentially reducing the time and cost associated with drug development and personalized medicine.
Pharmacy automation, fueled by AI, is set to transform medication management and reduce errors with a projected market worth $12.7 billion by 2028.
Details
Automation in pharmacies is driven by the growing number of prescriptions and the need to enhance safety and efficiency, particularly in hospital settings.
AI advancements in pharmacy include automated packaging, labeling, and prescription processing, significantly cutting down treatment delivery times.
A new study collaborates with Brigham and Women’s Hospital to explore AI’s role in managing polypharmacy challenges, potentially improving patient safety and reducing healthcare costs.
Why It Matters
Pharmacy automation can significantly aid oncologists and caregivers by streamlining medication management, reducing the risk of errors, and enhancing patient care efficiency. AI's ability to manage complex medication regimens offers critical support in addressing the challenges of polypharmacy among patients.
Two advanced, elusive AI chatbots reappear, outperforming previous models.
Details
The AI chatbots 'im-a-good-gpt2-chatbot' and 'im-also-a-good-gpt2-chatbot' returned with improved capabilities surpassing GPT-4.
These chatbots are only accessible randomly via LMSYS Chatbot Arena, increasing interest and speculation in the AI community.
Despite their mysterious origins and the lack of confirmation from OpenAI, these models are drawing significant attention for their enhanced performance.
Why It Matters
We’re likely watching the preamble to the launch of GPT-5, where sneak peaks, mysterious tweets and public scoffing are new tools to drive curiosity.
Generative AI (GenAI) emerges as the top AI technology utilized in enterprises, surpassing other AI methods in adoption rates.
Source: MidJourney for Fierce Networks
Details
A Gartner survey shows 29% of enterprises in the U.S., Germany, and the U.K. use GenAI, making it the most deployed AI solution.
GenAI is primarily integrated into existing applications like Microsoft’s Copilot for 365 or Adobe Firefly, preferred by 34% of users.
The biggest challenge to AI adoption is demonstrating the business value, with 49% of respondents identifying it as a barrier.
Why It Matters
Understanding GenAI's leading role and integration methods can help oncologists and caregivers streamline clinical processes and patient management, potentially easing workload pressures.
Researchers are increasingly using AI chatbots like ChatGPT to draft scientific papers, risking inaccuracies and fabricated data in published research.
Details
At least 60,000 scientific papers may have used language models to assist in writing, showing signs like unusual word choices.
AI tools often 'hallucinate' information, generating false data and citations that could compromise the integrity of scientific literature.
Even with AI assistance in grammar and syntax, there's a slippery slope toward more significant misapplications in research and peer reviews.
Why It Matters
Be like NASA. Treat AI as an “idiot savant,” consider what it suggests, but make the output your own.
A new Harvard research paper explores three kinds of helpful AI agents that are gaining traction in biology and medicine.
Details
The paper explores AI agents for robotic bench work, brainstorming, and experiment planning (tweet). What does this mean for you?
AI as a research assistant: Imagine having an AI tool that can analyze massive genetic datasets, identify potential drug targets, and even design experiments to test new therapies. This could significantly accelerate cancer research and lead to faster development of personalized treatments.
Precision medicine gets even more precise: AI agents could help oncologists identify the best treatment options for individual patients based on their unique genetic makeup and tumor characteristics. This could lead to better outcomes and fewer side effects for patients.
Less paperwork, more patient care: AI agents could handle many of the time-consuming tasks that currently burden oncologists, such as data analysis, literature review, and report writing. This could free up more time for oncologists to focus on what matters most: caring for their patients.
Why it Matters
AI is shifting from a focus on the latest and greatest model to the notion of agency, where AI systems become collaborative partners in everyday life.