The Rise of AI Tools

Recently, OpenAI launched GPT-4, and I must admit, I eagerly subscribed to ChatGPT Plus at $20/month. The experience has been nothing short of impressive. Kudos to OpenAI for making AI accessible to everyone!

In a similar vein, Google has introduced Bard, which offers access to its AI model, LaMDA, through a free waitlist. Another commendable effort!

However, the online discourse surrounding these advancements often disappoints. Many opinions seem to stem from individuals who haven’t actually engaged with the tools, relying instead on secondhand accounts that lack credibility.

A unique prize cabbage, as seen in Madrid. The significance? No clue, but it's fascinating! Photo by the author.

Rather than reiterate the imperfections of GPT-4 and LaMDA—like factual inaccuracies that still persist, albeit less flamboyantly than before—I want to emphasize two key points:

1. Always verify what you haven't tested yourself.
2. Stop reading about GPT-4 and LaMDA; instead, dive in and explore.

Engaging with these tools is crucial for self-improvement. Currently, GPT-4 and LaMDA stand as the pinnacle of AI productivity resources available to the public. Therefore, I urge you to invest time in understanding them practically—don’t just read about them; experience them firsthand. (Feel free to leave this article; I'll manage!)

The beauty of these platforms is their simplicity: you don’t need specialized training to start interacting with them. Just type your queries as you would in a messaging app:

• To access GPT-4, sign up for ChatGPT Plus ($20/month).
• To try LaMDA, register for Bard (free, though a waitlist may apply).

Jump right in! Experimentation is harmless, provided you refrain from sharing sensitive information.

Having both options available means my advice is amplified: try them both! Compare responses by copying text from one tool to the other. Instead of relying on hearsay, explore each to determine which better meets your needs.

Once you’ve explored, return for the next section of my article.

This was the initial output from a query I ran, reminiscent of a previous viral ChatGPT post. As a writer, I wouldn’t use this text as is, but it’s engaging enough for a constructive dialogue, enhancing my writing process. Feel free to compare the GPT-4 output with its predecessor.

Back from your exploration? Great! Now we can engage in a meaningful discussion. You may find yourself both impressed by its utility and unimpressed by the hype surrounding it.

Understanding Large Language Models (LLMs)

LaMDA and GPT-4 represent the cutting edge of large language models (LLMs), akin to the latest advancements in computer technology. The rapid evolution from last December’s ChatGPT to the features offered by ChatGPT Plus is striking. It’s my hope that this article ages as poorly as early praise for the first MacBook—innovation is relentless, and we can expect even more advanced LLMs to emerge.

It's vital to recognize the immense potential of LLM technology. Ignoring it would be a shortsighted career move, reinforcing the need for a hands-on approach.

The Importance of Personal Engagement

How often does a groundbreaking technology emerge that demands not only endorsement from C-suite executives but also requires their personal engagement?

One of the most remarkable aspects of the LLM revolution is that nearly everyone stands to benefit from its productivity enhancements. Yes, even CEOs should have these tools on their laptops, alongside their emails and casual games.

Reflecting on the past, I recall how secretaries in the 1970s were concerned about being replaced by machines—only to find their roles absorbed by their bosses. Managers, once reliant on dictation, began to embrace typing, effectively taking over many of their secretarial duties.

We’re on the brink of a similar transformation today. This isn't about machines replacing jobs; it’s about a significant boost in individual productivity, creating both opportunities and challenges for society as a whole.

As such, advocating for organization-wide adoption of LLMs without first experimenting with them yourself is particularly egregious. Don’t fall into that trap. Instead, engage with LLMs until they either surprise or disappoint you. This approach will provide a grounded understanding of their capabilities and limitations.

Even if you’re typically resistant to technology, now is not the time to sit on the sidelines. Whether GPT-4 proves to be a lasting tool or a passing trend, the broader category of LLMs merits exploration.

The user experience is incredibly straightforward: log in, type your text, and hit ENTER. Even if a superior LLM appears tomorrow, the time spent exploring today is invaluable.

There’s much more to discuss on this subject, and I’ll be continuing this conversation in a brief series. In my next article (subscribe to stay updated), I’ll address a hidden challenge that may hinder many organizations from adopting LLMs, despite the buzz surrounding them.

Thanks for reading! Interested in a YouTube course?

If you enjoyed this content and seek a fun, applied AI course suitable for both beginners and experts, check out this course I’ve created for your enjoyment:

P.S. Have you ever tried repeatedly clicking the clap button on Medium to see the outcome? Curious to find hands-on ML/AI tutorials? Here are some of my favorite quick walkthroughs:

• Vertex AI
• AutoML
• AI notebooks
• ML for tabular data
• Text classification
• Image classification
• Video classification

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