Naren Tallapragada, CEO of Tessel Bio, discusses the limitations and potential of AI in biology, emphasizing that while AI models like AlphaFold have advanced protein folding predictions, they cannot yet fully model biological systems such as cells or tissues. He highlights the importance of real data, as seen in successful startups like Fauna Bio and Enveda, which have built extensive databases to support their AI models. Tallapragada advocates for "augmented intelligence," where AI assists in guiding experiments, as a practical approach in drug discovery.
The article discusses the essential machine learning knowledge and skills expected from data scientists during interviews. It aims to provide a comprehensive guide for candidates preparing for data science interviews or looking to refresh their understanding of key topics. The author emphasizes the importance of having a solid grasp of machine learning concepts and offers resources, including tables, to aid in preparation.
Snowflake's industry predictions for 2024 highlight the challenges and advancements in the field of generative AI. Concerns include managing negative impacts such as job loss and deep fakes, while ethical AI guardrails are expected to emerge more rapidly than in past tech upheavals. Large language models (LLMs) will become more common, but smaller, specialized models (MLMs) will be favored for efficiency. AI will become an integral work assistant, boosting productivity by up to 30% for developers. Data engineering and science roles will evolve to be more critical and engaging, while BI analysts will need to uplevel their skills. The generative AI revolution will also drive the creation of new apps and experiences, with open source teams gaining more impact through AI assistance. The hallucination problem in AI is predicted to be largely solved, facilitating broader adoption in enterprise settings. Open source contributions to generative AI are expected to parallel corporate efforts, with significant developments in the field.
