Dall-E Mini, the AI-powered text-to-image generator has taken over the internet. With its ability to render nearly anything your meme-loving heart desires, anyone can make their dreams come true.
DALL-E 2, a portmanteau of Salvador Dali, the surrealist and Wall-E, the Pixar robot, was created by OpenAI and is not widely available; it creates far cleaner imagery and was recently used to launch Cosmpolitan’s first AI-generated cover. The art world has been one of the first industries to truly embrace AI.
The open-sourced miniature version is what’s responsible for the memes. Programmer Boris Dayma wants to make AI more accessible; he built the Dall-E Mini program as part of a competition held by Google and an AI community called Hugging Face.
And with great technology, comes great memes. Typing a short phrase into Dall-E Mini will manifest 9 different amalgamations, theoretically shaping into reality the strange images you’ve conjured. Its popularity leads to too much traffic, often resulting in an error that can be fixed by refreshing the page or trying again later.
If you want to be a part of the creation of AI-powered engines, it all starts with code. CodeAcademy explains that Dall-E Mini is a seq2seq model, “typically used in natural language processing (NLP) for things like translation and conversational modeling.” CodeAcademy’s Text Generation course will teach you how to utilize seq2seq, but they also offer opportunities to learn 14+ coding languages at your own pace.
You can choose the Machine Learning Specialist career path if you want to become a Data Scientist who develops these types of programs, but you can also choose courses by language, subject (what is cybersecurity?) or even skill - build a website with HTML, CSS, and more.
CodeAcademy offers many classes for free as well as a free trial; it’s an invaluable resource for giving people of all experience levels the fundamentals they need to build the world they want to see.
As for Dall-E Mini, while some have opted to create beauty, most have opted for memes. Here are some of the internet’s favorites:
no fuck every other dall-e image ive made this one is the best yet pic.twitter.com/iuFNm4UTUM
— bri (@takoyamas) June 10, 2022
There’s no looking back now, not once you’ve seen Pugachu; artificial intelligence is here to stay.
Facial recognition technology is getting better, and every industry from fast food to law enforcement is beginning to utilize it.
About six months ago, Chinese conglomerate Alibaba released technology that allows customers to pay for goods via facial recognition. The tech giant, now worth over 500 billion dollars, chose KFC as the testing ground for their new payment method; a logical move, considering Alibaba is invested in Yum! China, the company responsible for every KFC, Taco Bell, and Pizza Hut operating within the country. This "Smile to Pay" method is possible because of Face++, a company that focuses on facial and body recognition technology. And the commercial sector isn't the only area that's investing heavily in facial recognition tech in China. There are train stations in Beijing that use facial recognition (based off of government IDs) to print out tickets, and many office buildings (including Alibaba's headquarters) are phasing out key cards in favor of this newer security measure. Still, the most common usage of facial recognition –and possibly the most difficult to come to terms with– is the identification of potential criminals.
As early as last August, Chinese police forces in Hangzhou, a city with a population comparable to New York, began using surveillance cameras fitted with this technology to identify suspects. Recently, Chinese police officers began using electronic sunglasses fitted with facial recognition software. These glasses allow officers to access a database and pull up information on any person that comes into their line of sight. While this technology seems like it belongs in a Ridley Scott movie, it's here now. And it's important for us to recognize its political and social implications.
You don't have to be a luddite to spot the dangerous precedent set by this new technology. When police officers can access your personal data on the fly, it's certainly reasonable to wonder about your civil rights. Still, this technology doesn't seem to be the privacy-erasing apocalypse that haunts the dreams of libertarians everywhere. It's helped police officers in China identify people involved in kidnappings and hit and runs, as well as scammers using fake IDs. With regard to privacy, the pros to using this technology seem to outweigh the cons. Where this tech becomes an issue, is in its inability to deal with nuance. For example, authorities in Shenzhen City are using facial recognition to automatically issue fines (via text) to jaywalkers. This technology will also keep records on repeat offenders, and has the potential to affect their credit scores.
Officers in China review footage using facial recognition software
The issue this technology presents is similar to that of traffic cameras. Before they were banned in New Jersey, these cameras would issue tickets for running red lights and making illegal turns. The issue was, that these cameras were programmed to operate within the strictest possible parameters. They followed the law to a tee. Since the program was completely automated, there was no way for the cameras to look at each case individually. Tickets were shot out at a rapid clip, arriving by mail to anyone who so much as made a right turn a second after the light turned red. From a government funding standpoint, it was a slam dunk, and the towns that put these traffic cams up made a ton of money from issuing the tickets, but the public outcry against the cameras was huge. While China has a much more authoritarian social structure than we do in the States, it's doubtful that the people of Shenzhen City will embrace this new system of doling out fines.
A facial recognition programs scans the face of a passerby
As usual, the fundamental issue with this new tech isn't something deliberately insidious by design, nor is it the way in which it's used by law enforcement. The real problem, as is the problem with all automated technologies, is its inability to replicate human decision making. There's no amount of programming that will allow this technology to distinguish subtle differences between offenders. There's a reason why we shouldn't let algorithms run our police departments; it's impossible to account for the nearly infinite amount of variables that go into human behavior. While there are certainly patterns, if we rely too heavily on these machines, we set the precedent that their programming is superior to our officers' powers of deduction. Machines are fundamentally tools that help us complete jobs-they can't do the jobs for us.