Bryan Kirschner, VP of Strategy, DataStax
Bill Gates has seen (or, for that matter, caused) significant advances in technology, so I don’t take the contrarian stance lightly, but I’d like to point out that his view on the importance of AI is undeniable. I think the way you describe the epiphany is only half correct.
After being “in awe” of OpenAI’s GPT model, which passed the AP Bio exam, the model was asked a non-technical question: “What would you say to a father of a sick child?” Gates describes the results as follows: The whole experience was amazing. “
I have no objection to that. As a ChatGPT user, I’ve been impressed with the ability to get work done faster and to be more proactive about what I can do (“Tell me about Aristotle Roy Kent” prompt, ChatGPT’s abusive responded) “Ted Lasso” character with a sense of wonder).
But as we all shape our business strategy around the impact of generative AI, we’re doing a 180-degree shift from notions of “wonderful” and “wonderful” to “dedicated,” “predictable,” and “productive.” You also need to look at
That’s because a model trained on (for example) 10,000 sympathy cards or 1,000 eulogies seems to speak more sensitively, comfortingly, and better than most people can do on the fly, and it’s more appropriate. Because I absolutely expect you to give off a nice tone. Not at all surprising, at least to people from the cultural or religious backgrounds for which the original content was produced.
Considering all the risks of hallucinations and bad behavior from models trained on the open internet, generative AI strategies in all organizations should enable well-intentioned people to create benevolent AI tailored to specific situations. It’s about liberating your sexuality. Model fine-tuning performed “on top of” the underlying model requires less data, costs less, and can be completed quickly.
Marc Andreesen gives an inspiring example of what is technically well within reach.
Every child has an AI tutor who is infinitely patient, infinitely caring, infinitely knowledgeable, and infinitely helpful. AI tutors accompany children at every stage of their development, helping them reach their full potential with a machine version of infinite love.
The most successful organizations of tomorrow will have dozens or even hundreds of AIs working alongside or on behalf of human staff in a planned and constructive manner. Two of her operational concepts, ‘enthusiastic intern’ and ‘autonomous agent’, will help revitalize your journey.
AI as an “enthusiastic intern”
Business school professor and technologist Ethan Morrick describes what he found to be a very useful framework for thinking about generative AI: [rather] They are very nice people. “
And don’t think of AI as replacements for people already paying their salaries, but treat them like “enthusiastic interns” that help them be more productive.
This metaphor helps in two ways. First, the need for human oversight is always brought to the fore. Just as hiring and productively managing interns is a valuable ability for an organization, so is using ChatGPT, Microsoft’s CoPilot, and Google’s Bard. However, as with the most promising interns, this class of models cannot be blindly trusted.
Second, and also important, IT is not responsible for hiring finance and HR interns. Similarly, finance and HR (and all other departments) need to build their own capabilities while understanding how to use these tools to be more productive. Your job is closer to answering domain-specific staffing questions than IT questions.
This is a key bet on the road to productivity breakthroughs, ‘autonomous agents’.
productivity agent
Autonomous agents chain tools so that, given a goal, the AI creates a task, completes the task, creates a new task, reprioritizes the task list, completes a new top task, You can loop until your goal is achieved. (This is an excellent introduction to use cases, including an example of how something like Andreesen’s infinitely patient math tutor is constructed.)
But if you’re a CEO who wants to accelerate the realization of “AI for all,” spend 10 minutes with your executive team discussing how you can build a consumer-centric agent today. I recommend reading the explanation given by Ed Anuff. Here’s the important excerpt:
You want to build a deck in your backyard, so open your home improvement mobile application and ask them to create a shopping list. The application is connected to LLMs such as his GPT-4 and many data sources (the company’s own product catalog, store inventory, customer information, order history, and many other data sources) so that what the user does You can easily find out if Need to complete a DIY project. But you can do more than that.
You describe the dimensions and features you want your deck to include, and the application provides visualization tools and design aids. Since we know your zip code, we can tell which stores near you have the items you need in stock. Based on your purchase history data, we can also suggest that you may need a contractor to help with the work, and provide contact information for nearby professionals.
This kind of experience is more than just the future for customers. It must also be the future of all employees. How can AI help marketers track brands on social media? How can it help legal teams with contracts? How can I help?
Your functional teams and business units should start thinking and implementing autonomous agents today. There’s never been a better time to be productive than now. The technology is ready and waiting.
Learn more about how DataStax enables real-time AI here.
About Brian Kirshner:
Brian is the Vice President of Strategy at DataStax. For over 20 years, we have helped build and execute strategies for large companies looking for new ways to move forward and a future that is radically different from the past. He specializes in removing fear, uncertainty and doubt from strategic decision-making through empirical data and market sensing.
