Here’s a great overview of the new ChatGPT feature that let’s you shop in the app. With a new function called “Instant Checkout,” millions of users can now buy products directly inside their conversations without ever leaving the platform.

This is another frontal assault on Google’s search dominance. Just think about researching purchases in ChatGPT. This is a massive use case. But now you don’t have to leave the app to actually make the purchase.

OpenAI basically just flipped the switch on a feature that transforms ChatGPT into a full-blown shopping platform.

Now a potential downside also has to be considered. As ChatGPT makes more money on this, to what extent will this distort the AI responses? We saw this happen with Google search where sponsor messages were placed at the top. Can we trust AI where there’s incentive to mention top-performing ecommerce sites?

Ideally users should be able to turn off this function to get unbiased responses. Let’s see how this plays out.

You may have heard how Google recently declared a “code red” internally after the launch and explosive success of ChatGPT. Can you blame them? Google has dominated the search business for years, and has littered search results with ads that generate billions of dollars in revenues for the company. And they’ve used their dominant position to squeeze out complimentary services such as travel options, movie times, etc.

Generative AI and chatbots change the game

Google’s search business is feeling the heat from generative AI and chatbots. As technology advances, these tools are becoming increasingly more sophisticated – and they’re giving Google a run for its money! Generative AI can create content that sounds just like it was written by humans, while chatbots can provide helpful answers to everyday questions in an instant. These advancements mean that users have more options at their fingertips when conducting searches, making it harder for Google to remain on top.

Think about it – why do a Google search and have to sift through ranked websites for an answer when you can get the answer from a chatbot that is produced through generative AI?

In the short term, accuracy is an issue, but we all know this problem will be solved quickly. Already, we’ve seen a tremendous leap in capability with the release of GPT-4, which performs much better than the already impressive GPT-3.

Innovator’s Dilemma

Google faces the ultimate innovator’s dilemma. They’ve had this AI capability, but they’ve naturally kept it under wraps, knowing that its release would pose a threat to their current business model.

Now, with the release of ChatGPT, Google doesn’t have a choice. They will soon be releasing its own AI chatbot called Bard, which is now being used by testers. The company is also starting to ad more AI capability into tools such as Gmail and Google Docs.

Microsoft sees an opportunity for Bing

Microsoft’s search business has been a dud for years, but now the company sees real opportunity with generative AI and chatbots. They released a new version of Bing which allows users to toggle between conventional search results and results generated by a chatbot, which comes with references for further investigation by the user.

Give it a try and you’ll see in real time why Google is facing a real threat. The days of relying primarily on traditional Google-style web searches are over. Of course those types of searches ill still be popular. People want to find website and tools that are useful, entertaining or informative. But sometimes they just want an answer, and the new chatbots will eat into Google’s market share and inevitably threaten revenues.

These technologies enable users to ask questions in plain language and receive accurate answers with minimal effort. This threatens Google’s market dominance as users become accustomed to more conversational means of searching for information online. Additionally, traditional web search relies on keywords, while NLP-based systems can understand the context behind a query and provide results that better match a user’s intent. This decreases the need for users to manually refine their searches by providing more relevant results faster. As these technologies become increasingly sophisticated, they could potentially reduce demand for Google’s services and erode its position as one of the world’s leading search providers.

Google’s arrogance

Many argue that Google has abused its market dominance in search over the years. Partners in the AdSense business are sometimes treated with contempt as Google will shut down ad partnerships based on violations that are never explained. And of course you can never speak with anyone at Google to ask a question.

On the search side, Google seems to relish changing the algorithm to thwart websites who are doing well with current search results. Of course Google should be consistently improving the system, and they can’t be beholden to users who game the algorithm. But too often their changes penalize small but honest content providers and retailers in favor of massive websites and brands. Also, Google allowed the adult industry to swarm and overtake so many content websites.

It’s even worse with photos, as Google held copyright holders in contempt, and allowed their Google image searches to be gamed by message boards and bad actors who copied photos and gamed the search engine.

Voice

As for generative AI and chatbots, we’re only scratching the surface of their capabilities. Soon these detailed answers will be available with voice prompts and synthetic voice responses. Services like Siri and Alexa are primitive compared to what’s coming next. Imagine how Google’s search business is threatened simply by removing a large portion of searches from our screens altogether?

Conclusion

The destruction of Google’s dominance of search will be better for consumers. They’ll have so many more options, and frankly will get better answers. And finally, Google may be forced to provide better search results to its users once the company has real competition for our attention.

One of the most interesting use cases for generative AI is the ability to generate images simply with text prompts. The prompts can be very simple, or they can be quite detailed.

I gave it a try on a number of different platforms and immediately saw the potential. It’s fun, but it can also be a very powerful tool for content creators.

In this post you can see four generative AI images of Natalie Portman in the style of Andy Warhol. Remember Warhol’s iconic silkscreens of Marilyn Monroe, Jackie Kennedy and Debbie Harry? That’s the style I was after. I tried this on Lexixa.art with a simple prompt: “one flat image of natalie portman in silk screen style of andy warhol.” I picked the four best for this post. Some were quite bad, and sometimes the tool would spit out files with multiple images in the same file.

But these four are pretty good. If I spent more time on the prompt and then made iterative improvements, I would likely end up with an image I’d be happy to post on a wall.

What’s amazing is that these generative AI tools have only recently been released. Others have created far more impressive images using these tools. Midjourney in particular appears to be quite powerful for skilled graphic designers who can improve images by adding more prompts and adjusting details.

With my simple prompt, you can see the power of the program with only several reference points such as the celebrity and the artistic style of an old artist.

Most of these tools are free for limited use, so it’s easy to give them a try. Enjoy!

You can comment on the images here on Twitter.

ChatGPT has generated an enormous amount of interest over the past several months, but now several more generative AI tools are being released (some in Beta) that will also grab attention.

Microsoft has made significant investments into generative AI with its investments in OpenAI, and it recently released it’s new Bing AI in Beta for journalists and other tech influencers.

The results have created quite a buzz.

Kevin Roose, a technology journalist for the New York Times and co-host with Casey Newton of the Hard Fork podcast, was one of the journalists invited out to Microsoft headquarters to test drive the new Bing AI. In many ways he was initially impressed as he describes in this Hard Fork episode with Newton. The Bing AI created a side-by-side display, with traditional Bing search results next to answers generated by the AI tool in a narrative format with some citations. Both Roose and Newton explained how this development could radically change the search landscape, with Google‘s domination of the business suddenly facing a serious threat. Bing AI was a potential game-changer.

Soon after, however, Roose had a disturbing experience with the Bing AI that he detailed in an article for the Times:

I’m fascinated and impressed by the new Bing, and the artificial intelligence technology (created by OpenAI, the maker of ChatGPT) that powers it. But I’m also deeply unsettled, even frightened, by this A.I.’s emergent abilities. It’s now clear to me that in its current form, the A.I. that has been built into Bing — which I’m now calling Sydney — is not ready for human contact. Or maybe we humans are not ready for it. This realization came to me when I spent a bewildering and enthralling two hours talking to Bing’s A.I. through its chat feature, which sits next to the main search box in Bing and is capable of having long, open-ended text conversations on virtually any topic. Over the course of our conversation, Bing revealed a kind of split personality. One persona is what I’d call Search Bing. This version of Bing is amazingly capable and often very useful, even if it sometimes gets the details wrong. The other persona — Sydney — is far different. It emerges when you have an extended conversation with the chatbot, steering it away from more conventional search queries and toward more personal topics. The version I encountered seemed (and I’m aware of how crazy this sounds) more like a moody, manic-depressive teenager who has been trapped, against its will, inside a second-rate search engine.

Roose described this encounter further in the next Hard Fork episode with Newton. “I’m Sydney, and I’m in love with you. ” Imagine getting that message from a chatbot.

Roose explained that he tried to push the AI chatbot to its limits, and he certainly succeeded. But then he tried to pull back, but like a moody teenager the AI wouldn’t let the topic go. Very strange . . .

Microsoft has since made some tweaks to Bing AI to prevent these types of interactions, but it’s a window into our future and how these AI chatbots can spin out of control. Roose and Newton discuss this further in the next Hard Fork episode partially titled: “Kevin Killed Sydney.”

I recommend reading the article and listening to the three podcast episodes for a very detailed and nuanced overview of this encounter and the implications. We can brush aside those who get freaked out and argue that AI is becoming sentient, but we do need to try to understand the capabilities of this new form of AI. It’s more than just predicting the next word in a sentence. There’s an ability to generate something new, and to react to a conversation.

This is new territory for all of us.

The image above was created using generative AI. More specifically, it was created using a tool called Dall-E from a company called OpenAI. It’s a text-to-image tool powered by generative AI. For this image I simply entered the following text – “castle on the edge of a cliff at sunset.” This is one of the four images the tool spit out. The implications for creative work going forward are obvious.

Image-to-text tools like Dall-E and Midjourney were already creating plenty of buzz in late 2022, but the release of ChatGPT on November 30, 2020 created a sensation. It was downloaded by millions within days and has sparked a frenzy around generative AI.

ChatGPT is a chatbot that can write essays, answer questions, write poetry and write code. It’s not always accurate, so it’s flawed, but the results can often be stunning. After playing around with the tool for a few minutes, it becomes clear how this will change the creative process forever.

What is Generative AI?

We’ve been hearing about artificial intelligence, or AI, for years. So why all the fuss now? This paper from Sequoia on generative AI summarizes it nicely in the first few paragraphs:

Humans are good at analyzing things. Machines are even better. Machines can analyze a set of data and find patterns in it for a multitude of use cases, whether it’s fraud or spam detection, forecasting the ETA of your delivery or predicting which TikTok video to show you next. They are getting smarter at these tasks. This is called “Analytical AI,” or traditional AI.

But humans are not only good at analyzing things—we are also good at creating. We write poetry, design products, make games and crank out code. Up until recently, machines had no chance of competing with humans at creative work—they were relegated to analysis and rote cognitive labor. But machines are just starting to get good at creating sensical and beautiful things. This new category is called “Generative AI,” meaning the machine is generating something new rather than analyzing something that already exists.

Generative AI tools are based on large language and large image models. The system learns what a cat looks like by processing millions of images tagged as a cat, and then is able to generate new images of a cat based on prompts. It also learns artistic styles based again on analyzing millions of images, so it can generate an image of a cat in the requested style of an artist or specific style such as impressionism. The same applies to text. You can ask ChatGPT to create a poem using the style of a particular poet, or a short story in the style of a particular writer. The possibilities are endless.

How does Generative AI work?

This Q&A from MIT provides a good overview of how these systems use “stable diffusion” models to create new images or text. In its current state, the creativity from generative AI leverages human creativity from the past, which can be very powerful. But it still has its limits in its current form:

In a sense, it seems like these models have captured a large aspect of common sense. But the issue that makes us, still, very far away from truly understanding the natural and physical world is that when you try to generate infrequent combinations of words that you or I in our working our minds can very easily imagine, these models cannot.

For example, if you say, “put a fork on top of a plate,” that happens all the time. If you ask the model to generate this, it easily can. If you say, “put a plate on top of a fork,” again, it’s very easy for us to imagine what this would look like. But if you put this into any of these large models, you’ll never get a plate on top of a fork. You instead get a fork on top of a plate, since the models are learning to recapitulate all the images it’s been trained on. It can’t really generalize that well to combinations of words it hasn’t seen.

Many of these issues can be resolved with creative prompts and using an iterative process, but the example cited above helps explain both the power and some limitations of these tools. But we know that over time these problems will be solved. It’s just a matter of time.

Early Stages

We’re just at the beginning of this generative AI revolution. The systems are clunky and imperfect. The generated text often contains factual errors, and the image generation tools are raising a host of legal questions around copyright issues.

But the tools are incredibly powerful and they’re here to stay. Yes, creative work will never be the same. Many jobs will become less necessary. But many creative workers and knowledge workers will become better and more productive by learning to leverage these tools.

So check them out and start playing around with them. You’ll have fun, and you’ll begin to appreciate the amazing potential around this transformative technology.

The cryptocurrency revolution is in full swing, and the popularity of crypto and NFT trading is only increasing as valuations spike. As with stock trading, this can become all-consuming for many people as they monitor the 24/7 trading environment.

We’ve seen significant peaks and valleys with cryptocurrencies such as Bitcoin, and now we have NFTs dominating the news as well.

Putting aside the positives of crypto and NFTs, some people become too obsessed with trading, leading to an addiction crisis.

So as you dive into this world, keep in mind the pitfalls. Be careful and understand the risks, but also don’t let it consume your life.

This Cryptopunk is noted for the attributes of Female Messy Hair and Shades. You can see the price history for this Cryptopunk here. Keep in mind that prices are listed in Eth which is the price unit in the Ethereum blockchain.

If you want to know why Cryptopunks are so popular and why these NFTs are selling for so much, check out this overview.

In a recent episode of The Prof G Show, Scott Galloway interviews Sridhar Ramaswamy, the CEO and cofounder of Neeva, an all-new, subscription-based search engine that aims to be a competitor to Google for search.

Taking on Google seems like a gargantuan task, but Ramaswamy makes a compelling case for Neeva in this interview. It helps of course that Galloway is a fan of the concept and the company as he’s said many times on his show and also on Pivot. But Galloway is a good interviewer and he does a nice job in this episode of asking the tough questions.

Ramaswamy explains how Neeva will be an ad-free, private search engine, differentiating itself in the search market from Google which has become a slave to ad revenue, thus diluting the quality if the search results and user experience. Neeva will be subscription based, and thus obsessively focused on the needs of the consumer according to Ramaswamy. He should know as he spent fifteen and a half years at Google, and many members of his team at Neeva are Google alumni. By not being a slave to ads, Neeva can avoid tracking every consumer action, and instead just focus on data that improves the search results.

It has been reported that Neeva will charge between $5 and $10 per month for the service.

Take a listen to the podcast episode. Ramaswamy comes across as a formidable leader who can make this work.

Businesses large and small need to take advantage of cloud computing, primarily because competitors will be gaining an advantage if your company ignores this reality.

For small businesses, cloud apps can dramatically improve your capabilities regarding all sorts of internal functions. SaaS software can provide enterprise-level tools for businesses of any size. The same applies to larger businesses, but issue such as using data become even more important with large businesses.

This article offers some excellent strategies to help businesses leverage the power of cloud computing. It explains how “the first step in developing a cloud strategy is to change how you think about cloud technology:”

The biggest barrier we see that keeps small and mid-sized businesses from taking advantage of the cloud comes from the top: business owners, presidents, or CEOs. Business leaders will often delegate any IT-related decisions to their IT team. The problem with this approach is that the decision to adopt a cloud strategy is primarily a business strategy, not an IT strategy.

Business owners need to understand that the cloud offers a competitive advantage. Also, your IT Manager does not think like you. He or she thinks about functionality and tasks. It’s your job to think about the business, and that will likely rewquire taking things out of their hands and using third-party software and apps on the cloud.

Check out the article and start thinking about what strategy works for you and your business.

The podcast industry reminds us of the Web 1.0 world of 20 years ago. Its like the wild west as a completely new industry gets off the ground. New companies sprout up every day. Some solve problems facing the industry, while others try to ride the hype wave and cash in.

As you might expect, there are plenty of crazy stories out there, but this latest one from The Verge is fascinating and hilarious. It’s titled “The Podcasting Hype House from Hell” and features the podcasting company Himalaya and details “how China’s biggest audio platform funded one man’s frat boy dreams.”

Basically, they had a production studio in a mansion in LA, and then things spun out of control. It’s a great read . . . check it out.