AI Big Bets: New Players in AI are The ‘Old’ Tech Players

Artificial Intelligence (AI), Industry Trends
May 16, 2023

“There’s talk on the street it sounds so familiar

Great expectations everybody’s watching you

People you meet they all seem to know you

Even your old friends treat you like you’re something new

Johnny come lately

The new kid in town

Everybody loves you

So don’t let them down”

– Eagles, New Kid in Town

Wasn’t it was just yesterday when ChatGPT was the only place where you could go and ‘taste’ the future? AI’s iPhone moment?

Fame is fickle.

Now the new kid in town is the old kid in town: Google.

Yes, the AI landscape is constantly changing, with new players emerging all the time. But it turns out that some of the biggest names in AI are still the old guard.

In today’s newsletter, we will go over these new (old) kids in town, that are transforming the landscape.

Let’s dive in. (Plus I have a movie recommendation in the Wrap Up section)

In this edition

Goooogle
AI Big Bets
AI: go strategic or tactical?

1. Goooogle

At its annual I/O conference, Google announced a ton of new AI capabilities.

Google’s CEO, Sundar Pichai, mentioned AI a whopping 27 times during his keynote. And calmly added $56B to the company’s market capitalization.

By now, you might have seen this meme doing the rounds (video below) 🙂

At its annual I/O conference, Google announced a ton of new AI capabilities. Let me share some of them with an explanation around why this is such a big deal:

1. Google Bard one-ups ChatGPT: Google has made Bard fully available in 180 countries, it is FREE, and it can browse live internet. Bard is also getting public apps like Adobe, Instacart, and Khan Academy. (update: ChatGPT has announced live internet access, but only for Plus users).

2. Google’s search engine, now with AI: The new search experience includes AI-powered snapshots of key information to consider with links to dig deeper and suggested next steps. With a conversational AI, Google will unlock search as an engaging experience. This is similar to Microsoft’s Bing + OpenAI integration.

3. Vertex AI: These are new Google Cloud AI offerings powered by AI-optimized infrastructure — including new A3 Virtual Machines based on NVIDIA’s H100 GPU. (yes, the ones being sold on eBay for $40,000). It is releasing 3 new AI models on this platform: Imagen for image generation, Codey for code generation, and Chirp for accurate text-to-speech. This is similar to how Microsoft Azure is offering access to OpenAI’s API.

4. PaLM 2 is Google’s new LLM: Google just released PaLM 2, its answer to OpenAI’s GPT-4. In some benchmarks, PaLM 2 has shown superior results than GPT-4. PaLM 2 supports over 100 languages and can perform “reasoning,” code generation, and multi-lingual translation. It comes in four sizes: Gecko, Otter, Bison, Unicorn. Gecko is the smallest and can reportedly run on a mobile device.

5. Duet AI in Google Workspace for Business: Google is embedding the power of generative AI across all the Workspace apps with Duet AI including Gmail, Docs, Sheets, and Slides. This enables a conversational way for business users to use AI and drive productivity within their business documents.

What does this mean?

Google is playing to its strengths. And then some.

Google is equipping users with AI across the board: early adopters, Internet Users, Developers, and Business Users.

Google massive search engine market share gives it a phenomenal surface area in terms of public data availablity and understanding user intent.

One can only imagine the scale of training data that Google can provide it’s AI.

AI is shaping up to be a battle for the ages between Google and Microsoft….and probably a handful of other players as well. I’m looking at you *cough* Amazon *cough*.

All of this is even more interesting because a lot of today’s Generative AI trend can be traced back to Google’s Transformer white paper “Attention is all you need”.

2. AI Big Bets

There are massive bets happenings in AI right now that are being made by the (old) new kids.

In just this past week:

1. Sensing that there is insatiable demand for AI chips and rising costs, AMD and Microsoft are teaming up for ‘Athena’; a new AI chip to power Microsoft and OpenAI infrastructure. Microsoft has reportedly invested $2B in this project.

2. IBM released enterprise AI software ‘WatsonX‘, a studio for companies to create capabilities based on foundation models, generative AI and machine learning including pre-trained models.

3. Huggingface released two amazing projects: one is StarCoder, a collab with ServiceNow as a free alternative to Microsoft’s Github CoPilot. The other one is is Transformer Agents which is way to not just generate code based on text inputs but also execute that code.

What does this mean?

a. There is increased competition in multiple areas of AI whether it is computer or LLMs or AI platforms.

b. Increased competition will mean lower pricing, which is great for everyone except AI vendors 🙂

c. We are seeing innovation at scale in weeks rather than months and years.

Saddle up, we will be keeping pace with these developments as things are moving fast!

3. AI: Go Strategic or Tactical?

When things are moving this fast, it really begs the question: should we think about AI strategically (medium to long term) or tactically (immediate term).

It is a great question and my immediate reaction to it would be to go strategic. But that could be the absolute wrong move.

Recommendation: Go Tactical

A strategic approach to AI means having a long-term plan for how you’re going to use the technology. But the AI landscape is changing so quickly that it’s impossible to make a long-term plan that will still be relevant in a few years.

That’s why it’s better to be tactical when it comes to AI. A tactical approach means focusing on short-term goals and using AI to solve specific problems. This approach is more flexible and adaptable, and it will help you stay ahead of the curve.

For example, we are currently helping clients with AI discovery workshops that focus on identifying immediate term transformational opportunities that create ROI and efficiency.

As we identify these AI use cases, we are going back to our database and updating it. So far, we have identified over 500+ AI use cases through client work and industry research (free access).

Wrapping up: Movie Recommendation

With all this innovation going on, sometimes it’s refreshing to come across good old business stories.

Stories that have made their way into work folklore over the years.

One such story is Phil McKnight’s journey at Nike that he wrote in his book Shoe Dog. But the book barely mentions @Sonny Vaccaro who is probably one of the greatest sports marketers of all time. He is the person who got Michael Jordan into a contract with Nike that accelerated Nike from 9% marketshare to a market leader.

In the movie Air, Sonny’s gets due credit. in fact the move feels like it’s written from his point of view.