Assc. Director Data Science & Senior Inventor at UnitedHealth Group - a Fortune 4 Company
Dear companies, take care of your AI talent, especially the researchers. Researchers? Really? Aren't researchers the least influential people in the company? - They are the cost-centers. They do not directly sell to customers & so, do not generate revenue. And company has to fund them from profits - They live far away from reality. They do not know the "ground-truth". - They are not enterprising or charismatic like the #marketing & #sales' dashing & street-smart folks. - They cannot converse in normal language but are deep inside their narrow, un-understandable world. - Even if they do not exist in the company, the current product portfolio can be enough to sustain sales for years, or even decades. Look at ROLEX. Their watches are as mechanical as they were decades ago! Clearly their R&D budgets for adopting consumer-side emerging technologies are near-zero. - They help achieve company's Reduction in Force (RiF) targets. This is probably the only reason a company & its other employees may want them - for own survival. As they get hit first. So, why should companies care about their AI researchers, if at all they have them? The world has changed. They are one of the most influential people in the tech world and its only likely to increase with time. Why? We do not need every researcher to come up with a newer neural architecture or a different LLM, VLM or LMM. Right? That's true. But their role has just expanded and we still do not know. They are some of the best equipped people to manage the speed of current AI changes, naturally. Look, the AI world has been so rapidly advancing in the past 2 years that leaders are finding it difficult to keep track of them. Even if they succeed to keep track of them, their AI developments & implementations are becoming obsolete within 6-9 months! Ask a leader, and you'll invariably hear this. So? How will AI researchers help? They know the next in-thing (or likely to be one) at least a year before the world. And so, they can guide the next #AI #development or implementation within an organization that can sustain itself for a little over an year and a half, at least. Even if they are not implemented, at least the leaders & organizations can plan their 3-year strategies (Short Range Planning) based on their inputs. Are there any examples? AI Agents. They have been in existence for over an year. But organizations are still implementing LLMs. In spite of #Devin going viral! So tell me, what's the next in-thing that companies should think of? While there are nuanced answers to this question, some of the prominent ones, in general, would be - Natural Conversations, Reinforcement Learning & #Humanoids. But not every future in-thing actuates in future. No? True. And hence, we even need a Discriminator & not just a Generator AI researcher ^_^ #GAN #Future #HLM
Puneet sharma
1mo
Insightful
Vipul Chadha
1mo
Very helpful
Assc. Director Data Science & Senior Inventor at UnitedHealth Group - a Fortune 4 Company
1mo#HLM: Human Language Model - adopted from my dear friend & an adjunct professor at New York University Dr. Cesar Koirala.