INBOX INSIGHTS, July 24, 2024: How to Get Involved, What the Llama Model Means for AI - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: How to Get Involved, What the Llama Model Means for AI (7/24) :: View in browser

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How to Get Involved

Four and a half, almost five years ago, I wrote this post about how to get involved and volunteer your time. Given where the world is today, it feels like the right time to refresh it.

You can read the original post here.

I’m seeing a lot of people on social media asking how they can get involved, so I’ll offer a few suggestions.

Join a community

Whether it’s virtual or in-person, finding like-minded people is a great place to start. There are countless Slack, Discord, and social media groups that are passion-focused. If you’re interested in analytics and marketing (and AI and being unhinged) you can join our free Slack community, Analytics for Marketers.

In writing this, I learned that there are a lot of platforms where you can find your people. Some of which are newer to me! There is likely a group that shares your interests. Here are a couple of handy links to get you started:

Volunteer your time

Since writing the original post, I’ve started volunteering weekly at a local animal shelter. It’s only a couple of hours a week, but I know that while I’m there, I’m making a difference and helping the pups find forever homes. There is no shortage of organizations that will welcome people willing to donate their time. Volunteering doesn’t always have to be something that you do in person, either. You can offer up your professional skills as well. Volunteering is also a low-risk way to step outside of your comfort zone and try new things.

If you’re not sure where to start, check in with your town hall or library. They should have a list of local organizations looking for volunteers. If not, they can point you to additional resources. If you want to do your own research, here are a few websites you can start with:

Additionally, you can ask around in the communities that you join. Networking with your groups is the best way to find the right information.

I’ll keep it brief this week. Change happens when you get involved. If you’re spending your time on social media, share information and uplift others. Use your voice and your platform to educate. Find people you connect with and have shared interests. Getting involved with what you’re passionate about doesn’t have to look a certain way. Do what makes sense for you.

How are you getting involved? Reach out and tell me, or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative analytics, a new way to use AI to get more from your data. Discover why simply collecting data isn’t enough and how generative analytics helps you uncover actionable insights. Learn practical ways to apply this approach to your marketing efforts and avoid common analysis pitfalls. Finally, understand the importance of good data governance for getting accurate results from any AI-powered tool.

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we sat Katie in the Hot Seat and had her build programmatic prompts in generative AI. Catch the episode replay here!

This week, we’ll be looking at how to see if your real customer data matches up with your ideal customer profile data. Are you following our YouTube channel? If not, click/tap here to follow us!

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👉 New! Generative AI for Email Marketing!

In this week’s Data Diaries, let’s take a step back for a moment to talk grand strategy, generative AI, and the big picture. Yesterday, July 23, 2024, something profound happened.

Generative AI became a permanent feature for humankind.

Now, that sounds awfully bold and bombastic. Why? Up until yesterday, there have been two kinds of generative AI models: open and closed.

Closed models are the ones that power big services like ChatGPT, Claude, and Google Gemini. They’re gigantic foundation models that are incredibly capable, resource intensive, and locked down. You can’t go into the model and make changes, you can’t turn on or off certain features, and the inner workings of the model are opaque, closed to the world. You write prompts for them and hope they do what they’re supposed to do.

Critically, they’re 100% under a third party’s control, which means if a company like Anthropic or OpenAI went out of business, your access to those models goes with them.

Open models are ones that typically are smaller, lighter, and open for technical AI folks to download, alter, make changes, and customize. They’re usually less capable than the foundational closed models – after all, they have less data in them. But the tradeoff of being less capable was that you could run them on devices as small as a laptop, and run them inside your own infrastructure. For folks who need absolutely secure, private AI, this was the way to go – knowing that you’d lose some performance and capabilities in trade.

All that changed yesterday when Meta released Llama 3.1, the latest version of their open model. They released it in three sizes, 8B, 70B, and 405B; the B refers to the number of parameters in billions. More parameters means the model is more capable and skillful, at the expense of being more resource-hungry. An 8B model can run on just about any laptop. A 70B model can run on a beefed-up gaming laptop or a high-end machine.

The Meta Llama 405B model needs tens of thousands of dollars’ worth of hardware to run at reasonable speeds if you want to host it yourself. It’s really meant for organizations to use in server rooms, as opposed to something you or I would use.

But the 405B version performs at or above closed models in most artificial benchmarks, which is astonishing. No other open model has ever performed even close to state of the art, and Llama 3.1 405B beats the latest version of ChatGPT and the latest version of Anthropic Claude on more than half of artificial benchmarks.

What this means is that for the first time, an open foundation model has been released that’s competitive with closed models – and that means if a company set up their own infrastructure using Llama 3.1 405B internally, that company would have state of the art generative AI in perpetuity.

If OpenAI or Meta or Google or Anthropic vanished tomorrow, that model would still be in operation because it’s on your own servers, your own infrastructure. Generative AI – state of the art generative AI – would be yours to keep. It might never advance past that point, but today’s AI is already amazingly capable.

That’s what I mean when I say that the release of this model is SUCH a huge deal in the big picture. Generative AI is now permanent, immune to the tides of fortune for big tech providers. Any company willing to invest in the infrastructure can have generative AI on tap forever, no matter what happens to Silicon Valley.

And if you derive benefit from generative AI today, that means you’ll be able to continue deriving benefit from it, no matter what. The option to either host your own or switch providers will mean that generative AI will never go away and can never be fully taken away from you from now on.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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Imagine a world where your marketing strategies are supercharged by the most cutting-edge technology available – Generative AI. Generative AI has the potential to save you incredible amounts of time and money, and you have the opportunity to be at the forefront. Get up to speed on using generative AI in your business in a thoughtful way with our new offering, Generative AI for Marketers, which comes in two flavors, workshops and a course.

Workshops: Offer the Generative AI for Marketers half and full day workshops at your company. These hands-on sessions are packed with exercises, resources and practical tips that you can implement immediately.

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