Generative AI
10 Graphs That Sum Up the State of AI in 2023 - E-DeshSeba
The Stanford Institute for Human-Centered Artificial Intelligence (HAI) has assembled a year's worth of AI data providing a comprehensive picture of today's AI world, as they have done annually for six years. And I do mean comprehensive--this year's report came in at 302 pages. That's a nearly 60 percent jump from the 2022 report, thanks in large part to the 2022 boom in generative AI demanding attention and an increasing effort to gather data on AI and ethics. For those of you as eager to pour through the entire 2023 Artificial Intelligence Index Report as I was, you can dive in here. But for a snapshot of the entire set of findings, below are 10 charts capturing essential trends in AI today.
Doomsday to utopia: Meet AI's rival factions
Who is behind it?: Two leading AI labs cited building AGI in their mission statements: OpenAI, founded in 2015, and DeepMind, a research lab founded in 2010 and acquired by Google in 2014. Still, the concept might have stayed on the margins if not for the same wealthy tech investors interested in the outer limits of AI. Musk invested in DeepMind and introduced the company to Google co-founder Larry Page. Musk brought the concept of AGI to OpenAI's other co-founders, like CEO Sam Altman.
Cybercrime: be careful what you tell your chatbot helperโฆ
Concerns about the growing abilities of chatbots trained on large language models, such as OpenAI's GPT-4, Google's Bard and Microsoft's Bing Chat, are making headlines. Experts warn of their ability to spread misinformation on a monumental scale, as well as the existential risk their development may pose to humanity. As if this isn't worrying enough, a third area of concern has opened up โ illustrated by Italy's recent ban of ChatGPT on privacy grounds. The Italian data regulator has voiced concerns over the model used by ChatGPT owner OpenAI and announced it would investigate whether the firm had broken strict European data protection laws. Chatbots can be useful for work and personal tasks, but they collect vast amounts of data.
The man who unleashed AI on an unsuspecting Silicon Valley
As part of that job, he's planned a round-the-world goodwill tour to talk with politicians and people using OpenAI's technology. The month-long campaign -- which will take him to Canada, Brazil, Nigeria, Europe, Singapore, Japan, Indonesia and Australia, among other stops -- comes as debate over AI's impact on the world is heating up. The Italian government temporarily banned OpenAI in March, citing concerns about privacy and data collection.
We're Not Ready for the AI Boom. It's Coming Anyway.
It's been a whirlwind few months in the world of large language models (LLMs), better known to most people as chatbots. Since the release of ChatGPT by OpenAI in Nov. 2022, we've seen billions upon billions of dollars being poured into the development and implementation of generative AIs such as Google's Bard and Microsoft's Bing chatbots--and it's easy to see why. Chatbots like ChatGPT or image generators like DALL-E and Midjourney can feel like magic. With the right prompts, you can get it to do things you wouldn't have imagined a few years ago like craft late night monologue-ready jokes and creating award-winning pieces of "art." It's no surprise that since the public launch of ChatGPT, tech companies have been working to cash in on this modern-day gold rush.
Synthetic Data Is About To Transform Artificial Intelligence
Imagine if it were possible to produce infinite amounts of the world's most valuable resource, cheaply and quickly. What dramatic economic transformations and opportunities would result? This is a reality today. It is called synthetic data. Synthetic data is not a new idea, but it is now approaching a critical inflection point in terms of real-world impact. It is poised to upend the entire value chain and technology stack for artificial intelligence, with immense economic implications. Data is the lifeblood of modern artificial intelligence. Getting the right data is both the most important and the most challenging part of building powerful AI.
Creating GPT-Driven Applications Using LangChain
Large Language Models (LLMs) like OpenAI ChatGPT are called foundational models because even though they are trained for a relatively small set of tasks, they work exceptionally well for multiple unseen downstream tasks. While there is still some debate on how they are so good, at a high level it is quite easy to under what they do -- they just predict the next word (read tokens). And all the cool tools you see built using these models, are nothing but the smart application of this feature. All said and done, they are also quite infamous for a lot of things -- sometimes the generations don't make sense, the models hallucinate (generating the same things over and over again), generations are not factually correct, they can't do maths well, and more. While one research paradigm believes training bigger models with more data can fix some of these problems, another approach is to improve the existing model by connecting them with external apps.
OpenAI Threatened With Lawsuit Over ChatGPT Defamation
For the first time, OpenAI may face a lawsuit over ChatGPT-generated defamation. An Australian mayor named Brian Hood, who according to Reuters is peeved about the fact that ChatGPT wrongfully identified him as a guilty party in a "foreign bribery scandal involving a subsidiary of the Reserve Bank of Australia in the early 2000s," apparently claiming that Hood had even served prison time for his so-called crime. Hood was involved in the scandal -- but as the whistleblower, not the crime-doer. Yeah, we'd be pissed, too. Per Reuters, Hood's lawyers sent a "letter of concern" to OpenAI back on March 21 demanding that the company fix its chatbot's error within 28 days.
Top 5 Books to Find a Good Pace in the Universe of Generative AI
One of the most often used buzzwords in technology today is Artificial Intelligence. We're learning more and more about how computers can mimic human thought processes and even complete jobs that were once thought to be too tough for robots to complete thanks to innovations like Siri and Alexa. In a world where robots are getting cleverer by the day, this book is all about how humans and artificial intelligence can coexist. According to Russell, we may do this by reconsidering how we approach AI systems. One of his recommendations is to create computers that are unsure about human preferences, making them submissive and determined to put the interests of humans before their own.