AI Quick Bytes Unleashed: Navigating the Future with Jon Stewart's Wit and AI Insights
Robert Franklin, CSP
Founder & CEO, Journey To Agility | Breaking down Al strategies, trends and tools for all tech professionals and enterprises
Greetings to our AI Quick Bytes community!
Humor can be a sharp tool, and few wield it as effectively as Jon Stewart. When satire hits close to home, it can sting, especially when it pokes fun at topics near and dear to our hearts. Jon's incisive wit does raise some salient points that merit serious consideration. Diving into the conversation, an insightful viewer's comment on the below video caught my attention: "At 60, I've seen the dawn of computing. We were promised shorter workweeks; instead, I see people working more, not less." It brings us to the perennial debate: Is the apprehension surrounding AI justified? Are we facing a job crisis or are we on the cusp of job creation like never before? History shows us that each industrial leap has ultimately opened new employment avenues. What's your take on this? Let's discuss.
Quick Bits
Deeper Bytes
Strategy
Let's talk strategy in the midst of the AI revolution, where the pursuit of gold is not for the precious metal but for the transformative power of AI in business. The burning question, "Is there any substance behind the hype?" is astutely addressed in Forbes' latest piece, "Successful Real-World Use Cases For LLMs (And Lessons They Teach.)” This article skillfully illustrates the breadth of AI's influence across industries. Here’s a snapshot of the real-world examples highlighted:
Customer Service and Support:
Healthcare and Life Sciences:
Business and Market Analysis:
Testing and Data Generation:
As we navigate the future, the potential to leverage AI models and methods to amplify business results is boundless, limited only by our creativity. It is this very ingenuity that distinguishes us from Artificial Intelligence at this juncture. Our unique human capacity to pinpoint challenges and collectively mobilize an organization's strengths to harness AI for solutions is what truly sets us apart.
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Trends
In previous editions of AI Quick Bytes, we've highlighted the crucial importance of defining clear goals, objectives, outcomes, speed, and trust for the success of AI implementation initiatives. Mathis Lucka of Deepset takes these elements a step further in his illuminating presentation, "5 Steps to a Successful Gen AI Pilot." He has a talent for demystifying the intricate, as you can see in the above featured snippet where he tackles the prioritization of AI Use Cases. You might wonder, what does strategy have to do with trends?
Excellent query!
Trend Prediction
Having an internal Data Science/Engineering team is a luxury not every enterprise can afford. Those with the resources for such teams often struggle to navigate the AI lifecycle from discovery and prototyping to production efficiently, if at all. For Startups to Mid-Sized companies, where AI is not a foundational expertise, the pressure is on to quickly gain proficiency and make a meaningful impact. I advocate for the adoption of a SaaS platform like Deepset, which simplifies the complexity of developing LLM-powered applications. A reusable, standardized toolkit is essential, as it saves teams from the redundant toil of crafting and upkeeping an LLM platform. Remember, model training is just one of the myriad challenges in deploying LLM-driven applications. This discovery and iterative process of finding the right fit of AI tools to output value is reminiscent of David Bland's "Testing Business Ideas" methodology, which we've enthusiastically endorsed in a prior newsletter.?
Below are links to a videos that delves into each of the above steps. The victors in the race of AI innovation will be those who can swiftly and repeatedly iterate through this cycle, with the agility to deploy, monitor, and refine based on user feedback.
Tools
Poe is the Swiss Army knife of AI models, giving you the flexibility to test drive a diverse set of chatbots to discover your perfect match. It offers access to a suite of AI models including well-known names like ChatGPT, DALL-E-3, Anthropic, Gemini, and Llama.
In my early trials with Poe, I'm seeing its potential as a valuable asset alongside my paid ChatGPT account. It’s my go-to for more straightforward prompts, leaving the heavy lifting to the bespoke bots I’ve honed for specific tasks. There is a monthly fee to access top tier LLM’s with message limits for the lower quality models, but a great way to subscribe to multiple Chatbots and see which one works best for you.
Which Model do you like best?
Prompts
Want to become a wizard in Prompt Engineering? Skip the wand and head straight to the source: the OpenAI Prompt Engineering Guide. It's your spellbook to conjure up some seriously potent prompts.
"This guide shares strategies and tactics for getting better results from large language models (sometimes referred to as GPT models) like GPT-4. The methods described here can sometimes be deployed in combination for greater effect. We encourage experimentation to find the methods that work best for you.
Some of the examples demonstrated here currently work only with our most capable model, gpt-4. In general, if you find that a model fails at a task and a more capable model is available, it's often worth trying again with the more capable model.
You can also explore example prompts which showcase what our models are capable of."
ChatGPT Prompt Engineering
Try it out and share your favorite strategies / practices in the comments!
Great things are happening here!
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Until next time, take it one bit at a time!