4 Predictions for the AI Industry in 2024

Plus a $100B valuation and GPT store launch!

 👋 Hey there!

Welcome to the first newsletter of 2024. If you thought that AI moved quickly in 2023, expect things to move quicker in 2024.

Here’s what’s in store for today’s edition:

  • An updated format to the newsletter,

  • Where I think AI is going in 2024,

  • A break-through in the robotics industry,

  • and more…

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New here? Grab a cup of coffee - we’re talking AI here. This newsletter talks about how you can use AI to create solutions to problems, so if this sounds like your kind of thing, hit that “subscribe” button below!


Curated links to anything AI related

🚀 Boost your SEO rankings with Morningscore, the only SEO tool you’ll need. Manage your keywords, links, and monitor your site health (link).

✍️ 26 guiding principals for prompting language models such as ChatGPT (paper) (link).

🤖 Figure-01 robot was trained on how to make a cup of coffee in under 10 hours with learning how to correct itself (link).

🎨 Catch every design flaw with a Figma plugin: Design Buddy (link)

🏪 The GPT store will be launching this week (link).

📰 NIST publishes a “best AI security” 106 page publication (link).


🚨 I need your help with something…

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In 2023, the AI industry moved very swiftly. For example, ChatGPT went from a free research preview to being able to customize your GPT in under 1 year.

Since last edition was laid out ChatGPT’s lifetime since last year, I wanted to take the first edition of this newsletter and give you 4 of my predictions for what I think is going to happen in the AI industry in 2024.

» I do want to take a second and highlight Morningscore, an SEO management tool that helps me, as a developer, better my website for Google searches. They provide a comprehensive and interactive dashboard to help me manage my keywords and links and sends me reports to let me know how I’m doing SEO-wise. Get started for free for 14 days!

Let’s dive into the predictions.

Prediction #1: Robotics will begin to stand out amongst the crowd

While we have seen amazing strides with AI, robotics has been semi-quietly churning in the background.

There’s a huge gap in the labor force in the USA, and I believe that robotics will help fill this gap once we widely adopt this kind of technology.

OpenAI is working towards AGI, which is, in essence, where AI can think like a human (versus being a text predictor, like ChatGPT is). When AGI is achieved, we’ll see it being implemented in robotics.

This leads me to my second prediction:

Prediction #2: AGI has a fair chance at being achieved

Rather than seeing this as the final destination, it should be looked at as a milestone. OpenAI is nearing this point, but it’s something that will take years before it’s public-facing.

The most recent round of funding for OpenAI is at $100B 🤯 having access to this kind of money allows for innovative research. Pair this with the best AI researchers… … you know where I’m going with this.

This is something that OpenAI has been working towards internally.

Prediction #3: Generative AI applications will stabilize, most will phase out

When ChatGPT was released, a huge opportunity had presented itself to implement a generative language model to specific use cases (coding, education, etc) - you may have heard of the term “fine tuning”.

However, a lot of these applications are simply “GPT wrappers”; think of them as an application that doesn’t really solve an issue.

In fact, I wrote an edition on whether if AI is the solution to help solve your problem. Turns out that AI isn’t necessary the majority of the time - it’s a buzz word.

Applications that don’t bring any value to the market will fade. I think this is an excellent opportunity for larger AI companies to discuss acquisition for not the product, but to build out their email list for marketing.

Prediction #4: Hardware requirements to train will lower

While this may seem like an obvious prediction because over time, algorithms will become more efficient, there’s one important factor that is often overlooked: the environment.

The current state of the hardware to train AI models is not environmentally sustainable.

The carbon footprint that comes about from training these models is quite concerning; oh the irony. Electronic waste also is a problem, as hardware does degrade over time.



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