🦾How You Can Leverage:

A random email landed in Gary Rivlin's inbox in late 2022.

From Reid Hoffman.

Yes, THAT Reid Hoffman.

His message? Machines would finally speak OUR language.

On today's Everyday AI show, Silicon Valley journalist and author of the new book AI Valley, Gary Rivlin shared his two-year deep dive interviewing the architects of our AI future.

He's seen this movie before (hello, .com bubble!), but this time it's on FAST FORWARD.

• So is GenAI the most overhyped tech ever?

• Or is it the underhyped?

• And more importantly….how can we all cash in on it?

Gary dished all, so make sure you go read/watch/listen to the full show.

And now, on for the 3 big insights. 👇

Remember 1997?

Gary does.

He was reporting from the frontlines when Amazon was just "that online bookstore."

Now he's experiencing intense déjà vu. VCs are throwing STUPID money at anything with "AI" in the pitch deck.

Two Google engineers team up with a Meta researcher, write a memo, and suddenly raise $10 million on a $100 million valuation.

Without.

A.

Product.

Ilya Sutskever (OpenAI's co-founder) launched Safe Superintelligence and secured BILLIONS with a $32 BILLION valuation.

Again, with no actual product. But unlike the .com era, this time the pace is FRANTIC.

The internet took decades to reshape our world and AI is doing it in months.

Try this

Find ONE workflow in your business that devours time and target it with AI.

Example: using Runway's tools and cut a team’s workflow from 60 people to 15-20 while slashing timelines from 16 weeks to 6 weeks.

They didn't replace creatives – they supercharged them. Start small, measure results, expand from there. Your first AI win should solve a specific problem, not your entire business model.

Here's the WILDEST part of the AI gold rush.

Silicon Valley is betting the farm on something most people fear.

Less than one-third of Americans are excited about AI.

The rest? TERRIFIED or totally meh or just kinda confused.

Yet Big Tech keeps shoving chips to the center of the table. Like…. HUNDREDS of BILLIONS of dollars in chips. (Both figuratively and literally with GPUs)

Gary’s seen this seemingly bizarre disconnect before. He points to classic VC FOMO – Jim Breyer once invested $12 million in Facebook when everyone thought he was NUTS. That bet turned into many of BILLIONS.

Now everyone's terrified of missing "the next Facebook" of AI.

The result? A casino atmosphere where PowerPoint decks are like pulls of a rusty Vegas slot machine, with flimsy startups securing obscene checks just because they’ve got Ex-Big Tech in their title.

Gary warns this will trigger a "boomerang effect" – some inevitable AI disaster that turns public sentiment even more negative.

Like… what could go wrong with VCs betting blindly ont he next AI hit like Drunk Chads in Vegas?

Try this

Create an "AI Trust Framework" for your organization TODAY.

Draft a simple document outlining what data your AI tools can access, what they cannot do, and how you're protecting users. Share it with customers. When the inevitable AI scandal hits your industry, you'll be the thoughtful player who prioritized safety.

This is your insurance policy against the "boomerang effect" Gary predicts is coming.

 The economics of frontier AI are INSANE.

Training costs in early 2023: tens of millions.

Today? BILLIONS.

By 2027, Anthropic's CEO told Gary they'll need nearly $100 BILLION for their next model.

Gary's shocking conclusion? The next Google will just be…… Google. lolz.

Not because they're better at building AI, but because they're the only ones who can afford it. We're headed toward MORE tech concentration, not less.

Sorry small startups.

Try this

Copy Runway's playbook. This AI video company competes with OpenAI and Google despite being founded by three artists, not PhDs.

Their edge?

Deep domain expertise. 

Identify what you know about your industry that tech giants don't. Find an AI use case that requires this insider knowledge. Build a focused solution for that niche. You don't need better foundation models – you need to apply AI to domains you deeply understand in ways tech giants can't.

This is your ONLY path forward in the age of $100 billion AI development budgets.

Apparently we just fast-forwarded 10 years into the AI future. 

While us normal humans are all talking about AGI, or Artificial General Intelligence, superhuman Sam Altman just dropped a blog post on super intelligence. 

Why’s that a big deal? 

That’s what we talked about today on Everyday AI. 

After all, y’all wanted it!

// poll results screenshot // 

Well, when arguably the most important person in AI says that we’re a ‘few thousand days’ away from superintelligence, we gotta pay attention. 

Because it's not every day the CEO of a trillion-dollar-backed AI company predicts the end of human intelligence supremacy.

You didn’t come here to learn? 

Then you’re in the wrong place shorty!

Kidding aside, we gotta start elementary AI to truly understand what Sam Altman is talking about when referencing super intelligence. Here’s the most oversimplified version: 

AI: The OG. Traditional machine learning and deep learning AI has been around since the '50s. It's your credit card approvals and Netflix recommendations.

GenAI: The new kid on the block. Generative AI has burst onto the scene thanks to powerful Large Language Models like ChatGPT and friends. Fresh faced and popularized in 2022. It's AI that creates stuff - text, images, code, you name it. 

ANI: Artificial Narrow Intelligence. AI that's better than humans at one specific thing. Like IBM Deep Blue defeating Garry Kasparov in chess in 1997 or IBM Watson winning  Jeopardy! in 2011. 

AGI: The holy grail. The ever-moving target. This is an AI that's as smart as humans across the board. We're not there yet, but we're closer than you think. 

ASI: The final boss. AI that's smarter than all humans combined in every way. This is what Altman's talking about, and it's either utopia or Skynet.

Try this: 

Alright, now that you’ve got the definitions and a loose definition of what’s what, go give Sam’s piece a first read. 

Or a second read. 

What’s at the heart of any communication professional’s role? Know your audience, and appeal to them with spot-on communication. Megan broke down an absolute gem of an example — engagement surveys. 

Her old approach? Having to manually search and analyze in a sea full of data. Her new approach? Getting the job done in a fraction of time with Generative AI. 

Try this:
Oh, that sounds legit, right? Analyzing spreadsheets and combing through stacks of data in seconds. 

(I waaaaaaant that!)

We’ve gotchya covered here. 

Here’s how to analyze data in ChatGPT like a consultant, and how to make ChatGPT’s Advance Data Analysis mode respond to your customers for you. 

Next-level strategy to make yourself irreplaceable? 

Change your job responsibilities. 

Megan dished on her approach and best advice for communication professionals. 

If GenAI tools become more skilled at your day-to-day tasks, change your day-to-day responsibilities. 

Try this:
Megan suggested shifting your responsibilities to take on more of a focus on productivity, creativity and strategy.

Check out this detailed article on the future of communications roles in the age of AI, and how you can make AI more of a companion than a competitor.