Lifeboat Foundation

New AI systems released in 2023 demonstrate remarkable properties that have taken most observers by surprise. The potential both for positive AI outcomes and negative AI outcomes seems to have been accelerated. This leads to five responses:

1.) “Yawn” — AI has been overhyped before, and is being overhyped again now. Let’s keep our attention on more tangible issues.

2.) “Full speed ahead with more capabilities” — Let’s get to the wonderful positive outcomes of AI as soon as possible, sidestepping those small-minded would-be regulators who would stifle all the innovation out of the industry.

Type: departments.

careers.

Harvard.

Continue reading “This Harvard Law Professor is an Expert on Digital Technology” »

Keep your eye on the prize, but meanwhile don’t lose sight of other nifty opportunities too. What am I talking about? During the famous Gold Rush era, eager prospectors sought the dreamy riches of unearthed gold. Turns out that very few actually struck it rich by discovering those prized gold nuggets. You might be surprised to know that while panning for gold, there was a possibility of finding other precious metals. The erstwhile feverish desire to get gold would sometimes overpower the willingness to mine silver, mercury, and other ores that were readily seen while searching for gold.

It all has to do with data, particularly data mined or scanned from the Internet that is then used principally to data train generative AI apps.

OpenAI’s ChatGPT and its successor GPT-4 would not exist if it were not for all the data training undertaken to get the AI apps into shape for doing Natural Language Processing (NLP) and performing interactive conversations with humans. The data training entailed scanning various portions of the Internet, see my explanation at the link here. In the case of text-to-text or text-to-essay generative AI, the mainstay of ChatGPT, all kinds of text were scanned to ferret out patterns of how humans use words.

Continue reading “Internet Training Data Of ChatGPT Can Be Used For Non-Allied Purposes Including Privacy Intrusions, Frets AI Ethics And AI Law” »

In the wake of the AI-generated hit Heart on My Sleeve going viral with deepfakes of multi-platinum artists Drake and The Weeknd, pop star Grimes has invited her fans to create music with her voice.

On Sunday night she tweeted, “I’ll split 50% royalties on any successful AI generated song that uses my voice. Same deal as I would with any artist i collab with. Feel free to use my voice without penalty. I have no label and no legal bindings.”

Continue reading “Grimes Tells Fans To Deepfake Her Music, Will Split 50% Royalties With AI” »

Like many people, you may have had your mind blown recently by the possibility of ChatGPT and other large language models like the new Bing or Google’s Bard.

For anyone who somehow hasn’t come across them — which is probably unlikely as ChatGPT is reportedly the fastest-growing app of all time — here’s a quick recap:

Continue reading “Auto-GPT May Be The Strong AI Tool That Surpasses ChatGPT” »

In this talk, De Kai examines how AI amplifies fear into an existential threat to society and humanity, and what we need to be doing about it. De Kai’s work across AI, language, music, creativity, and ethics centers on enabling cultures to interrelate. For pioneering contributions to machine learning of AIs like Google/Yahoo/Microsoft Translate, he was honored by the Association for Computational Linguistics as one of only seventeen Founding Fellows worldwide and by Debrett’s HK 100 as one of the 100 most influential figures of Hong Kong. De Kai is a founding Professor of Computer Science and Engineering at HKUST and Distinguished Research Scholar at Berkeley’s ICSI (International Computer Science Institute). His public campaign applying AI to show the impact of universal masking against Covid received highly influential mass media coverage, and he serves on the board of AI ethics think tank The Future Society. De Kai is also creator of one of Hong Kong’s best known world music collectives, ReOrientate, and was one of eight inaugural members named by Google to its AI ethics council. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

Over the past year or so, generative AI models such as ChatGPT and DALL-E have made it possible to produce vast quantities of apparently human-like, high-quality creative content from a simple series of prompts.

Though highly capable – far outperforming humans in big-data pattern recognition tasks in particular – current AI systems are not intelligent in the same way we are. AI systems aren’t structured like our brains and don’t learn the same way.

Continue reading “Networks of Silver Nanowires Appear to Learn And Remember Like The Human Brain” »

Pneumonia is a potentially fatal lung infection that progresses rapidly. Patients with pneumonia symptoms – such as a dry, hacking cough, breathing difficulties and high fever – generally receive a stethoscope examination of the lungs, followed by a chest X-ray to confirm diagnosis. Distinguishing between bacterial and viral pneumonia, however, remains a challenge, as both have similar clinical presentation.

Mathematical modelling and artificial intelligence could help improve the accuracy of disease diagnosis from radiographic images. Deep learning has become increasingly popular for medical image classification, and several studies have explored the use of convolutional neural network (CNN) models to automatically identify pneumonia from chest X-ray images. It’s critical, however, to create efficient models that can analyse large numbers of medical images without false negatives.

Now, K M Abubeker and S Baskar at the Karpagam Academy of Higher Education in India have created a novel machine learning framework for pneumonia classification of chest X-ray images on a graphics processing unit (GPU). They describe their strategy in Machine Learning: Science and Technology.

Facebook and Instagram owner Meta will release a commercial A.I. product, following moves from Google, Microsoft, and OpenAI, in 2023 confirmed Reality Labs boss Andrew Bosworth.