The Berkeley Innovation Group
We transform organizations using an experiential learning approach, infusing design-thinking capabilities throughout the company's culture.
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Our clients engage us because they say we make them feel “comfortable,” with innovation. They describe our co-creation process as “collaborative,” “refreshing,” and “engaging,” while calling their outcomes “eye-opening,” “culture-changing,” and “an outsized return on investment.” Contact us to learn more!
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The Berkeley Innovation Group
"Pay attention to what people are ready to say."
Leadership strengthens when we treat voice as a signal worth listening for not just in confident updates or polished presentations, but in the moments when someone feels safe enough to question, push back, or sit with uncertainty out loud.
I've watched this play out the same way across classrooms and startups. The room that invites curiosity is the room that performs. The team that welcomes dissent is the team that innovates.
A simple practice for today:
Notice who hasn't spoken yet.
Ask one genuine question.
Listen fully before you respond.
That's awareness in action and it quietly changes leadership outcomes.
👉 If this resonates and you're navigating similar dynamics in your classroom or organization, I'd welcome the conversation.
biginnovates.com/
4 weeks ago | [YT] | 0
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The Berkeley Innovation Group
This week, Google made a quiet but meaningful shift: separating chips for training AI models from those designed to run them in real-world use.
It may sound like infrastructure detail.
It’s actually about how AI performs inside a business.
Training a model is intensive, but it happens in cycles.
Running it powering copilots, workflows, and AI agents happens continuously. That’s where speed, cost, and reliability start to matter.
Google’s direction reflects that reality: optimize for what runs every day, not just what gets built.
At the same time, Amazon, Microsoft, and Meta are all investing in their own AI chips while still working with Nvidia.
This isn’t about replacing one player.
It’s about designing systems that fit specific workloads.
For leaders, this is where the conversation becomes more grounded:
AI in production introduces new constraints.
• Cost per interaction becomes visible
• Response time shapes user experience
• Scale exposes inefficiencies quickly
What works in a pilot often behaves very differently at scale.
The shift isn’t dramatic, but it’s important:
AI moves from something you experiment with to something your business depends on operating well and that changes how decisions get made.
www.biginnovates.com
4 months ago | [YT] | 0
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The Berkeley Innovation Group
AI becomes powerful when leaders move from understanding it to building with it.
I’m co-hosting a hands-on executive session with Jill Nickels, in partnership with Vistage, the world’s leading executive coaching organization.
𝐘𝐨𝐮𝐫 𝐅𝐢𝐫𝐬𝐭 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭 - 𝐁𝐮𝐢𝐥𝐭 𝐛𝐲 𝐲𝐨𝐮, 𝐟𝐨𝐫 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬
In one focused session, you will:
• Build an AI agent tailored to your workflows
• Develop a clear approach on leading AI adoption across your team
• Walk away with a practical 30-day action plan
This is not a seminar. It’s a working session for leaders ready to apply.
Designed for a small group of C-level executives.
📍 May 4, 2026 | Berkeley
📩 Message me to RSVP
#JeffEyet #TheBerkeleyInnovationGroup #AI #Leadership #ExecutiveEducation #Berkeley #Vistage #AIAdoption
4 months ago | [YT] | 1
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The Berkeley Innovation Group
Every week, I get the same question:
“𝙄𝙨 𝙞𝙩 𝙨𝙩𝙞𝙡𝙡 𝙬𝙤𝙧𝙩𝙝 𝙡𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝘼𝙄 𝙣𝙤𝙬 𝙩𝙝𝙖𝙩 𝙚𝙫𝙚𝙧𝙮𝙤𝙣𝙚 𝙝𝙖𝙨 𝙖𝙘𝙘𝙚𝙨𝙨 𝙩𝙤 𝙞𝙩?”
𝗦𝗵𝗼𝗿𝘁 𝗮𝗻𝘀𝘄𝗲𝗿: 𝗮𝗰𝗰𝗲𝘀𝘀 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗲 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲, 𝗷𝘂𝗱𝗴𝗺𝗲𝗻𝘁 𝗶𝘀.
That’s exactly why this program filled faster than expected.
Most people are learning tools.
Very few are learning how to think with them.
So we opened a second section.
If you’re serious about not just using AI but leading with it this is worth a closer look.
Spots will move quickly again.
👉 Take a look at the details and see if it fits where you’re heading. classes.berkeley.edu/content/2026-summer-engin-170…
𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐡𝐞𝐫𝐞 calcentral.berkeley.edu/
4 months ago | [YT] | 1
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The Berkeley Innovation Group
Most parents are focused on whether their child is using AI.
A better question is:
What kind of thinking habits is AI reinforcing?
Tools like ChatGPT and Google Gemini are becoming a student’s default thinking partner. And that shapes more than homework.
It shapes:
𝘞𝘩𝘦𝘯 𝘵𝘩𝘦𝘺 𝘵𝘳𝘶𝘴𝘵 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯
𝘞𝘩𝘦𝘯 𝘵𝘩𝘦𝘺 𝘲𝘶𝘦𝘴𝘵𝘪𝘰𝘯 𝘪𝘵
𝘞𝘩𝘦𝘯 𝘵𝘩𝘦𝘺 𝘳𝘦𝘭𝘺 𝘰𝘯 𝘵𝘩𝘦𝘮𝘴𝘦𝘭𝘷𝘦𝘴
Research from places like MIT shows students tend to accept confident AI answers even when they’re wrong.
Over time, that builds a habit: outsourcing judgment.
So the goal for parents isn’t control.
It’s guidance.
Ask:
“𝗪𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝘆𝗼𝘂 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝗶𝗻 𝘁𝗵𝗶𝘀 𝗮𝗻𝘀𝘄𝗲𝗿?”
“𝗪𝗵𝗲𝗿𝗲 𝗰𝗼𝘂𝗹𝗱 𝘁𝗵𝗶𝘀 𝗯𝗲 𝘄𝗿𝗼𝗻𝗴?”
Because AI ethics at home isn’t about limiting tools.
It’s about raising someone who knows when to trust them and when to think for themselves.
www.biginnovates.com
4 months ago | [YT] | 1
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The Berkeley Innovation Group
A quiet shift is happening in high schools right now.
Two students can turn in equally polished work
one understands it, the other doesn’t.
AI makes them look the same.
That’s the part most parents don’t see.
The real risk isn’t misuse.
It’s false confidence when students believe they’ve learned something they’ve actually outsourced.
Over time, that gap shows up in how they:
𝘦𝘹𝘱𝘭𝘢𝘪𝘯 𝘵𝘩𝘦𝘪𝘳 𝘵𝘩𝘪𝘯𝘬𝘪𝘯𝘨
𝘩𝘢𝘯𝘥𝘭𝘦 𝘢𝘮𝘣𝘪𝘨𝘶𝘪𝘵𝘺
𝘮𝘢𝘬𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 𝘢 𝘵𝘰𝘰𝘭
And that’s what school and life will eventually demand.
So the question isn’t whether your child uses AI.
It’s whether they can stand behind the work without it.
www.biginnovates.com
4 months ago (edited) | [YT] | 0
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The Berkeley Innovation Group
𝐀 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐰𝐚𝐲 𝐭𝐨 𝐬𝐜𝐚𝐥𝐞 𝐀𝐈 𝐢𝐬 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠.
While many teams focus on building more powerful models, Meta is showing what happens when you rethink how intelligence is applied.
Their Adaptive Ranking Model doesn’t treat every decision the same.
It adjusts in real time matching the level of model complexity to the actual need.
It’s a small shift in design, but a meaningful one:
✦ Less unnecessary computation
✦ Better use of infrastructure
✦ Strong performance at sub-second speed
And the impact shows: +3% conversions, +5% CTR.
What I find most interesting isn’t just the engineering.
It’s the mindset.
AI isn’t only about making models more powerful.
It’s about applying that power with precision.
This is where many organizations are starting to focus now:
→ Where does deeper intelligence truly add value?
→ Where can simpler systems do the job just as well?
That clarity is what turns AI from an experiment into something operational.
If you’re thinking through how to design AI systems that are both effective and efficient, I’m always happy to exchange perspectives.
www.biginnovates.com
#JeffEyet #TheBerkeleyInnovationGroup #AI #BusinessStrategy #AIForBusiness #MachineLearning #Leadership #Innovation
4 months ago | [YT] | 1
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The Berkeley Innovation Group
𝐀 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐰𝐚𝐲 𝐭𝐨 𝐬𝐜𝐚𝐥𝐞 𝐀𝐈 𝐢𝐬 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠.
While many teams focus on building more powerful models, Meta is showing what happens when you rethink how intelligence is applied.
Their Adaptive Ranking Model doesn’t treat every decision the same.
It adjusts in real time matching the level of model complexity to the actual need.
It’s a small shift in design, but a meaningful one:
✦ Less unnecessary computation
✦ Better use of infrastructure
✦ Strong performance at sub-second speed
And the impact shows: +3% conversions, +5% CTR.
What I find most interesting isn’t just the engineering.
It’s the mindset.
AI isn’t only about making models more powerful.
It’s about applying that power with precision.
This is where many organizations are starting to focus now:
→ Where does deeper intelligence truly add value?
→ Where can simpler systems do the job just as well?
That clarity is what turns AI from an experiment into something operational.
If you’re thinking through how to design AI systems that are both effective and efficient, I’m always happy to exchange perspectives.
www.biginnovates.com
#JeffEyet #TheBerkeleyInnovationGroup #AI #BusinessStrategy #AIForBusiness #MachineLearning #Leadership #Innovation
4 months ago | [YT] | 1
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The Berkeley Innovation Group
Parents: before your child heads to college, there’s one thing I’d want them to understand about AI.
Not how to use it.
How to lead with it.
Because right now, most students are learning prompts.
Very few are learning judgment.
They can generate answers in seconds
But struggle to ask better questions
They can produce polished work
But don’t always understand what makes it good
That gap matters.
In a world where AI can do the execution,
the real advantage shifts to something deeper:
» Thinking clearly
» Making decisions with incomplete information
» Knowing when to trust AI and when not to
» Taking responsibility for the final outcome
That’s leadership.
And it’s not being taught enough.
The students who will stand out in college and beyond won’t be the ones who use AI the most.
They’ll be the ones who:
𝘊𝘩𝘢𝘭𝘭𝘦𝘯𝘨𝘦 𝘪𝘵
𝘋𝘪𝘳𝘦𝘤𝘵 𝘪𝘵
𝘐𝘮𝘱𝘳𝘰𝘷𝘦 𝘰𝘯 𝘪𝘵
𝘈𝘯𝘥 𝘬𝘯𝘰𝘸 𝘸𝘩𝘦𝘯 𝘵𝘰 𝘪𝘨𝘯𝘰𝘳𝘦 𝘪𝘵
If you’re a parent, don’t just ask: “Is my child using AI?”
Ask: “Is my child thinking better because of it?”
That’s the difference between dependency and leadership.
And it starts earlier than most people think.
🔥 If this is something you’re thinking about whether as a parent, educator, or school leader I’m always open to exchanging perspectives.
4 months ago | [YT] | 1
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The Berkeley Innovation Group
A professor I spoke with recently tried something different.
He didn’t ban AI.
He redesigned the assignment around it.
Students were allowed to use AI to generate the first draft of their essays.
But that wasn’t the real work.
The real assignment was this: 𝗖𝗿𝗶𝘁𝗶𝗾𝘂𝗲 𝘁𝗵𝗲 𝗔𝗜’𝘀 𝘁𝗵𝗶𝗻𝗸𝗶𝗻𝗴.
» 𝘞𝘩𝘦𝘳𝘦 𝘥𝘰𝘦𝘴 𝘵𝘩𝘦 𝘢𝘳𝘨𝘶𝘮𝘦𝘯𝘵 𝘧𝘢𝘭𝘭 𝘢𝘱𝘢𝘳𝘵?
» 𝘞𝘩𝘢𝘵 𝘢𝘴𝘴𝘶𝘮𝘱𝘵𝘪𝘰𝘯𝘴 𝘢𝘳𝘦 𝘩𝘪𝘥𝘪𝘯𝘨 𝘶𝘯𝘥𝘦𝘳𝘯𝘦𝘢𝘵𝘩?
» 𝘞𝘩𝘢𝘵’𝘴 𝘮𝘪𝘴𝘴𝘪𝘯𝘨, 𝘪𝘨𝘯𝘰𝘳𝘦𝘥, 𝘰𝘳 𝘰𝘷𝘦𝘳𝘴𝘪𝘮𝘱𝘭𝘪𝘧𝘪𝘦𝘥?
» 𝘞𝘩𝘢𝘵 𝘩𝘢𝘱𝘱𝘦𝘯𝘦𝘥 𝘯𝘦𝘹𝘵 𝘤𝘩𝘢𝘯𝘨𝘦𝘥 𝘵𝘩𝘦 𝘥𝘺𝘯𝘢𝘮𝘪𝘤 𝘰𝘧 𝘵𝘩𝘦 𝘤𝘭𝘢𝘴𝘴𝘳𝘰𝘰𝘮.
Students spent less time trying to sound smart…
and more time actually thinking.
They challenged ideas.
They questioned outputs.
They debated each other.
The conversations got sharper. More honest. More alive.
AI didn’t make them lazy. It raised the bar.
Because the job was no longer to produce answers.
It was to interrogate them.
That’s the shift most institutions are still missing.
We’re moving from a world where value came from creating content…
to one where value comes from evaluating, refining, and directing thinking.
If assignments, workflows, and teams are still designed for the old model,
AI will feel like a shortcut.
Redesign them, and it becomes something else entirely:
A thinking partner that exposes gaps, not just fills pages.
This is the real opportunity in education and far beyond it.
The question isn’t whether people are using AI.
It’s whether they’re being taught how 𝘁𝗼 𝘁𝗵𝗶𝗻𝗸 𝘄𝗶𝘁𝗵 𝗶𝘁.
👉 If you’re exploring how to redesign learning, team workflows, or client delivery in this new reality, I’m always open to exchanging perspectives.
www.biginnovates.com
4 months ago | [YT] | 2
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