Little bit about the our first Workplai product
- The purpose of Taskai - the first AI product of Workplai is the solve informational tasks for small and midsized businesses. Thousands of businesses process information as their primary product. Our mission is to solve and then automate these tasks with custom AI solutions
Yes
Energy/Power is going to be the primary constraint for AI growth, IMO.
We might have to have a few years where, like the internet in the early 2000s, the value proposition and ecosystem is not fully built.
We'll have some organizations adopting it early and really pioneering AI. These organizations will have a massive advantage.
The other laggards will view AI as disappointing. Some call this the pit of despair or the "chasm" when a new technology is being adopted and suffers a temporary setback.
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At Workplai, we custom design AI systems for your organization based off your proprietary data. Using multiple AI agents, which solve portions of your work process, we group the agents together in workflows.
The real value of AI is in efficiency gains and time savings. We discovered that a custom AI system can save 25% - 75% of time per task.
In a competitive environment, AI could be the difference between dominating your industry and going out of business. Our mission is the help businesses and organizations dominate this next technological leap.
If interested in the full presentation, I'll fill you in on where AI is at the moment, where it's going, and how we are positioning to win.
Cursor screwed up so bad that I had to quit for a few weeks just to figure out how to handle the fallout and where to go next.
Yet, we march on.
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Building, Building, Building
- Commoditization of LLMs means value will be built on top of models
- Any tool that doesn't have a model toggle will not compete.
- Thesis: The smaller the problem solved by an agent, the more accurate the solution
- Thesis: Companies with proprietary knowledge need customization which includes their data in the AI
The best AI solutions are User Interfaces that customize your unique solutions.
- Ease of Use for your Employees
- Visuals and Dashboards to track performance for Leadership
- All of your Organizational Tasks and AI Solutions in One Place
All in one User Interface. Taskai
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A quality AI product should enhance the capability of commoditized LLMs. A truly custom AI solution.
- Building of Custom Agents
- Categorized and Saved Tasks and Prompts
- Multiple AI Models
- Accuracy Feedback Scoring and Improvement Loop
- Task Manager for Automation
- Security Built-In for 100% Secured Data
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Beware the new Gell Mann Amnesia Effect when it comes to AI.
One of my favorite phenomena of cognitive bias, Gell Mann Amnesia, describes how consuming media is a vastly different experience when you fully understand an issue vs. when you are an outsider.
The concept was coined by novelist Michael Crichton in a 2002 speech, naming it after Murray Gell-Mann, a Nobel Prize-winning physicist with whom he had discussed the phenomenon.
"Briefly stated, the Gell-Mann Amnesia effect is as follows. You open the newspaper to an article on some subject you know well. In Murray's case, physics. In mine, show business. You read the article and see the journalist has absolutely no understanding of either the facts or the issues. Often, the article is so wrong it actually presents the story backward—reversing cause and effect. I call these the "wet streets cause rain" stories. Paper's full of them.
In any case, you read with exasperation or amusement the multiple errors in a story, and then turn the page to national or international affairs, and read as if the rest of the newspaper was somehow more accurate about Palestine than the baloney you just read. You turn the page, and forget what you know."
— Michael Crichton, "Why Speculate?" (2002)
Mike Ginn, a writer, discovered something similar happening with AI.
"Its amazing how chatgpt knows everything about subjects I know nothing about, but is wrong like 40% of the time about things Im an expert on. Not going to think about this any further."
AI is very smart at gathering data from public sources and distilling that information in an easy to understand way, which helps us learn.
But in topics where we know a great amount of detail from experience and study, AI will often fall short. Why is this? The nuance and experience it takes to become an expert at any given topic is greater than publicly available knowledge on the internet.
Nuanced or experiential knowledge is the guy who has worked for 20 years and just knows that when X happens, to do Y. It's not written down anywhere or collected in any database. He or she just understands.
What lesson can we learn here? AI is a tool. AI can give us a working knowledge of a subject matter but for the foreseeable future, it will not be able to have the full knowledge and experience of an expert in any field, and that's great news.
AI is a tool for us to use to be better at our work tasks, processes and responsibilities. It's important to understand how to use it and how not to use it. It's important to understand how to increase AI accuracy.
The smart human isn't going anywhere in this new AI world. AI will only expand the capabilities of what is possible.
its amazing how chatgpt knows everything about subjects I know nothing about, but is wrong like 40% of the time about things im an expert on. not going to think about this any further
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AI has the unique quality where you believe at the same time it can do everything and nothing for you.
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I make progress in AI and then watch a video where it seems like everyone else has already done it.
It's ok, I think there is value in creating your own workflow and framework solutions if you are solving specific business problems
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In my B2B AI business, have discovered B2C applications.
My issue now is not the product, but the marketing. Never tried to market a product B2C.
I'm allergic to advertising and I don't have big network type of mentality. Seems important now.
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