My hypothesis is that we’ll become so distrustful of content on the internet that we’ll only read content generated by people or brands we trust.
Many startups already use AI to generate children’s, fan fiction, romance, and fantasy books. Unlike traditional books, AI-generated books can be interactive, as a book’s plot can change depending on a reader’s preference. This means that readers can actively participate in creating the story they are reading. A children’s reading app identifies the words that a child has trouble with and generates stories centered around these words.
Sayfa 23 - O'Reilly Media
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Bir yıl boyunca verilen emeklerin ardından şimdi dinlenme, keşfetme ve yeni maceralara atılma zamanı. 🌞
Bu yaz bol kahkahalı, bol anılı ve elbette bol kitaplı geçsin. Tüm öğrencilere keyifli tatiller diliyoruz! 💙📖
Like many business decisions, building an AI application is often a response to risks and opportunities. Here are a few examples of different levels of risks, ordered from high to low:
1. If you don’t do this, competitors with AI can make you obsolete. If AI poses a major existential threat to your business, incorporating AI must have the highest priority. In the 2023 Gartner study, 7% cited business continuity as their reason for embracing AI. This is more common for businesses involving document processing and information aggregation, such as financial analysis, insurance, and data processing. This is also common for creative work such as advertising, web design, and image production. You can refer to the 2023 OpenAI study, “GPTs are GPTs” (Eloundou et al., 2023), to see how industries rank in their exposure to AI.
2. If you don’t do this, you’ll miss opportunities to boost profits and productivity. Most companies embrace AI for the opportunities it brings. AI can help in most, if not all, business operations. AI can make user acquisition cheaper by crafting more effective copywrites, product descriptions, and promotional visual content. AI can increase user retention by improving customer support and customizing user experience. AI can also help with sales lead generation, internal communication, market research, and competitor tracking.
3. You’re unsure where AI will fit into your business yet, but you don’t want to be left behind. While a company shouldn’t chase every hype train, many have failed by waiting too long to take the leap (cue Kodak, Blockbuster, and BlackBerry). Investing resources into understanding how a new, transformational technology can impact your business isn’t a bad idea if you can afford it. At bigger companies, this can be
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An AI model is only as good as the data it was trained on. If there’s no Vietnamese in the training data, the model won’t be able to translate from English into Vietnamese. Similarly, if an image classification model sees only animals in its training set, it won’t perform well on photos of plants.
The enterprise world generally prefers applications with lower risks. For example, a
2024 a16z Growth report showed that companies are faster to deploy internal-facing
applications (internal knowledge management) than external-facing applications
(customer support chatbots), as shown in Figure 1-8. Internal applications help companies
develop their AI engineering expertise while minimizing the risks associated
with data privacy, compliance, and potential catastrophic failures. Similarly, while
foundation models are open-ended and can be used for any task, many applications
built on top of them are still close-ended, such as classification. Classification tasks
are easier to evaluate, which makes their risks easier to estimate.
Sayfa 19 - O'Reilly Media
A drawback of supervision is that data labeling is expensive and time-consuming. If it costs 5 cents for one person to label one image, it’d cost $50,000 to label a million images for ImageNet.5 If you want two different people to label each image—so that you could cross-check label quality—it’d cost twice as much. Because the world contains vastly more than 1,000 objects, to expand models’ capabilities to work with more objects, you’d need to add labels of more categories. To scale up to 1 million categories, the labeling cost alone would increase to $50 million.