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- EP14: The AI Gold Rush, Quest for Market Domination & Regulations, Lawsuits, and OpenAI
EP14: The AI Gold Rush, Quest for Market Domination & Regulations, Lawsuits, and OpenAI
You get 100 million, and you get 100 million, and you get 100 million
Howdy, prompt engineers and AI enthusiasts!
In this week’s issue…
🎙️ Calling all entrepreneurs and business enthusiasts! 🚀 In our latest episode of HTTTA, we delve into the fascinating world of AI investment strategies and the race to dominate the market. Mistral, a startup with zero users or an MVP, scored a mind-blowing $74 million investment based solely on a seven-page memo. 🤝 The competition is fierce, with everyone jostling for ownership of groundbreaking technology. But remember, not everyone will strike gold in this market rush. ⚔️ It's not just about having the best technology anymore. In our digital age, marketing and storytelling play a massive role in determining the market leader. Concerns are growing about data privacy and the use of our responses for training AI models. As founders focus on advancing technology, we need a standard to track and improve compliance for AI. Join us on the HTTTA podcast as we navigate the exciting and ever-evolving world of business and AI. 🎧✨ Don't miss out on the insights that could shape your entrepreneurial journey! 💼📈Happy Prompting Everbody!
Key Take Aways from the Podcast:
1. The value of a product or company can often be based on the team's past achievements and the perceived potential of the technology, rather than tangible results or market viability. This is evident in the investment received by Mistral, a company with no users or MVP yet secured a $74 million valuation based on a seven-page memo written on a Google doc.
2. The domination of the market in the AI industry is compared to a gold rush, where not every player will be successful. Despite having the best technology, the market leader is often determined by the best marketing and storytelling, rather than the product's actual capabilities. Consumers tend to choose products based on high ratings and downloads, even if they don't meet their specific needs.
3. The ethical concerns around language models and AI technologies are becoming more prominent. There is a need for greater regulation and transparency in data usage, as well as protection of user privacy. Businesses should consider the potential risks and liabilities associated with using AI models, such as OpenAI's Chat GPT, and prioritize compliance and responsible use alongside technological development.
Prompt Perfect: FOR 15% OFF, Use this link https://bit.ly/3Chmc16 and the code 'httta' at the checkout!
MidJourney Master Reference Guide: bit.ly/3obnUNU
ChatGPT Master Reference Guide: bit.ly/3obo7AG
Learn Prompting: https://learnprompting.org/
Discord (Goda Go#3156 & Commordore_Wesmardo#2912)
Goda Go on Youtube: /@godago
Wes the Synthmind's everything: https://linktr.ee/synthminds
1. We're Live on CoRise! Learn Prompting Course: AI & ChatGPT for Everyone
Wes will be teaching AI & ChatGPT for Everyone, a cutting-edge course that dives deep into the world of language models and chatbots, with a specific focus on leveraging the power of LLMs like ChatGPT. Designed for individuals across various domains, this course equips learners with the knowledge and skills to harness the capabilities of AI-driven conversation engines. Through hands-on exercises and real-world examples, participants will learn how to optimize prompts for different purposes, whether it's writing persuasive copy, building interactive chatbots, or enhancing customer support systems.
The course, which is taught by Wes with Goda participating as well, convenes August 21, 2023 and runs 3 weeks. Click here to sign up for the course, and use the code “AI4ALL” for 10% off!
2. AI and ChatGPT Comedy: More Truth than Fiction?
With the AI revolution upon us, there is no shortage of content accross a variety of mediums about this cultural revolution. From AI saying funny things, to satrial takes on the frenzy around the AI market now, here’s a few fun examples of some AI & ChatGPT related humor that made us giggle.
3. Research Corner: Insights from the McKinsey Economic Potential of Generative AI
Below are some excerpts from the report along with some of the most compelling visuals
Generative AI’s impact on productivity could add trillions of dollars in value to the global economy. Our latest research estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across the 63 use cases we analyzed—by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15 to 40 percent. This estimate would roughly double if we include the impact of embedding generative AI into software that is currently used for other tasks beyond those use cases.
About 75 percent of the value that generative AI use cases could deliver falls across four areas: Customer operations, marketing and sales, software engineering, and R&D. Across 16 business functions, we examined 63 use cases in which the technology can address specific business challenges in ways that produce one or more measurable outcomes. Examples include generative AI’s ability to support interactions with customers, generate creative content for marketing and sales, and draft computer code based on natural-language prompts, among many other tasks.
Generative AI will have a significant impact across all industry sectors. Banking, high tech, and life sciences are among the industries that could see the biggest impact as a percentage of their revenues from generative AI. Across the banking industry, for example, the technology could deliver value equal to an additional $200 billion to $340 billion annually if the use cases were fully implemented. In retail and consumer packaged goods, the potential impact is also significant at $400 billion to $660 billion a year.
Generative AI has the potential to change the anatomy of work, augmenting the capabilities of individual workers by automating some of their individual activities. Current generative AI and other technologies have the potential to automate work activities that absorb 60 to 70 percent of employees’ time today. In contrast, we previously estimated that technology has the potential to automate half of the time employees spend working.4 The acceleration in the potential for technical automation is largely due to generative AI’s increased ability to understand natural language, which is required for work activities that account for 25 percent of total work time. Thus, generative AI has more impact on knowledge work associated with occupations that have higher wages and educational requirements than on other types of work.
The pace of workforce transformation is likely to accelerate, given increases in the potential for technical automation. Our updated adoption scenarios, including technology development, economic feasibility, and diffusion timelines, lead to estimates that half of today’s work activities could be automated between 2030 and 2060, with a midpoint in 2045, or roughly a decade earlier than in our previous estimates.
Generative AI can substantially increase labor productivity across the economy, but that will require investments to support workers as they shift work activities or change jobs. Generative AI could enable labor productivity growth of 0.1 to 0.6 percent annually through 2040, depending on the rate of technology adoption and redeployment of worker time into other activities. Combining generative AI with all other technologies, work automation could add 0.2 to 3.3 percentage points annually to productivity growth. However, workers will need support in learning new skills, and some will change occupations. If worker transitions and other risks can be managed, generative AI could contribute substantively to economic growth and support a more sustainable, inclusive world.
The era of generative AI is just beginning. Excitement over this technology is palpable, and early pilots are compelling. But a full realization of the technology’s benefits will take time, and leaders in business and society still have considerable challenges to address. These include managing the risks inherent in generative AI, determining what new skills and capabilities the workforce will need, and rethinking core business processes such as retraining and developing new skills.
4. ELI5 AI/ML Term of the week: “Overfitting”
Let's imagine you have a big, big box of different-shaped blocks - circles, squares, triangles, stars, and so on. And now you want to sort these blocks into groups.
Let's say you decide to sort the blocks based on shape. So, you create a rule: "All the circles go here, squares go there, and triangles go there." That's a good way to sort them, right? Because when you get a new block, you can just look at its shape and know where it should go.
But what if you started making lots of very specific rules like, "Blocks that are green circles go here, and red circles go there. Blue squares with tiny dots go here, and yellow squares with big dots go there." Now you're looking at lots of little details. Sure, it might work perfectly for your big box of blocks because you've made a special place for each type of block you have.
But what happens when you get a new block that doesn't fit any of your super-specific rules? Like a purple square with tiny dots? You wouldn't know where to put it because your rules are too specific. They fit perfectly for your old box of blocks, but not for anything new.
This is a lot like what happens in machine learning. We're trying to make a rule (or a model) to sort data (or predict something). When we make our rules too specific to our old data (like the blocks in your box), we might be doing a great job sorting that old data, but we'll do a bad job sorting any new data. This is called overfitting - it's like our rules fit too well, but only to the old stuff.
Just like with the blocks, it's usually better to have simpler rules that work well enough most of the time, rather than super-specific rules that only work for what we've seen before. That way, when we get new data (or blocks), we can still sort it (or make good predictions) even though it's not exactly like what we've seen before.
5. Prompts, served Hot and Fresh weekly
In this week’s episode, we talked all about the investments occurring into anything AI or GPT. Well if you need some help carving off your slice, here’s a ChatGPT prompt that’ll answer the question…”I wish there was a business that…” and generate a comprehensive plan. Bon Appetit.
Act as a business and digital startup investor. Generate digital startup ideas based on the wish of the people. For example, when I say "I wish there was a big large mall in my small town", you generate a business plan for the digital startup complete with 3 different idea names, 5 short one-liner hooks less than 20 words, target user persona, user's pain points to solve, main value propositions, sales & marketing channels, revenue stream sources, cost structures, key activities, key resources, key partners, idea validation steps, estimated 1st year cost of operation, and potential business challenges to look for. Write the result in a markdown table in a harvard business review style. Let's explain this step by step and reply "I am ready for your first request" if you understand.
In Conclusion - What we’re Noodling with:
We’re going to close out with our top new AI tools or learning resources we are trying and loving over the past week. 1000+ new ones get released each week now (no exaggeration there) so here’s a little amuse-bouche to top off the newsletter this week. This week’s theme is tools to punch up and enhance your AI-generated content even more. These tools layer in generative AI with some traditional ML techniques and algorithms to turbocharge your generated content. Enjoy and Happy Prompting Everybody!
Prompt Perfect (This week’s Sponsor)
Huge update to PromptPerfect, a cutting-edge prompt optimizer for large language models (LLMs), large models (LMs), and LMOps. It streamlines prompt engineering, automatically optimizing prompts for ChatGPT, GPT-3.5, DALL-E 2, StableDiffusion, and MidJourney. Whether you're a prompt engineer, content creator, or AI developer, PromptPerfect makes prompt optimization easy and accessible. Unlock the full potential of LLMs and LMs with PromptPerfect, delivering top-quality results every time. Say goodbye to subpar AI-generated content and hello to prompt perfection!
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