AI is Silicon Valley’s last-ditch attempt to avoid a stock market wipeout
Silicon Valley has entered the Hail Mary phase of its business cycle — a desertic part of a tech-industry downturn where desperation can turn into recklessness.
The biggest players of the last decade are facing an existential crisis as their original products lose steam and seismic shifts in the global economy force them to search for new sources of growth. Enter generative AI — algorithms like the viral program ChatGPT that seem to mimic human intelligence by spitting out text or images. While everyone in Silicon Valley is suddenly, ceaselessly talking about this new tech, it is not the kind of artificial intelligence that can power driverless cars, or Jetson-like robot slaves, or bring about the singularity. The AI that companies are deploying is not at that world-changing level yet, and candidly, experts will tell you it’s unclear if it ever will be. But that hasn’t stopped the tech industry from trying to ride the wave of excitement and fear of this new innovation.
As soon as it was clear that OpenAI, the creator of ChatGPT, had a cultural hit, it was off to the races. Read More
Monthly Archives: May 2023
50 AI Prompt Examples for Marketers to Use in 2023
As artificial intelligence advances, more businesses are interested in AI-powered solutions to improve their marketing efforts. One of the keys to making the most of the tech in marketing is to write effective AI prompts to generate the desired outcomes.
Marketers need to know how to communicate their goals effectively to AI systems. It’s a new skill that requires an understanding of how to write clear, concise, and effective instructions that a machine can understand. — Read More
PaLM2
When you look back at the biggest breakthroughs in AI over the last decade, Google has been at the forefront of so many of them. Our groundbreaking work in foundation models has become the bedrock for the industry and the AI-powered products that billions of people use daily. As we continue to responsibly advance these technologies, there’s great potential for transformational uses in areas as far-reaching as healthcare and human creativity.
… Building on this work, today we’re introducing PaLM 2, our next generation language model. PaLM 2 is a state-of-the-art language model with improved multilingual, reasoning and coding capabilities.
… At I/O today, we announced over 25 new products and features powered by PaLM 2. That means that PaLM 2 is bringing the latest in advanced AI capabilities directly into our products and to people — including consumers, developers, and enterprises of all sizes around the world. Read More
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Constitutional AI: RLHF On Steroids
AIs like GPT-4 go through several different1 types of training. First, they train on giant text corpuses in order to work at all. Later, they go through a process called “reinforcement learning through human feedback” (RLHF) which trains them to be “nice”. RLHF is why they (usually) won’t make up fake answers to your questions, tell you how to make a bomb, or rank all human races from best to worst.
RLHF is hard. The usual method is to make human crowdworkers rate thousands of AI responses as good or bad, then train the AI towards the good answers and away from the bad answers. But having thousands of crowdworkers rate thousands of answers is expensive and time-consuming. And it puts the AI’s ethics in the hands of random crowdworkers. Companies train these crowdworkers in what responses they want, but they’re limited by the crowdworkers’ ability to follow their rules.
In their new preprint Constitutional AI: Harmlessness From AI Feedback, a team at Anthropic (a big AI company) announces a surprising update to this process: what if the AI gives feedback to itself? — Read More
Meta open-sources multisensory AI model that combines six types of data
Meta has announced a new open-source AI model that links together multiple streams of data, including text, audio, visual data, temperature, and movement readings.
The model is only a research project at this point, with no immediate consumer or practical applications, but it points to a future of generative AI systems that can create immersive, multisensory experiences and shows that Meta continues to share AI research at a time when rivals like OpenAI and Google have become increasingly secretive.
The core concept of the research is linking together multiple types of data into a single multidimensional index (or “embedding space,” to use AI parlance). This idea may seem a little abstract, but it’s this same concept that underpins the recent boom in generative AI. Read More
IBM takes another shot at Watson as A.I. boom picks up steam
It’s been a long time since IBM has actively touted Watson. Originally created to beat humans at the “Jeopardy!” game show, Watson marked IBM’s early splash in artificial intelligence, but it never amounted to a profitable offering.
About 15 months ago, IBM sold its Watson Health unit for an undisclosed amount to private equity firm Francisco Partners.
Now, Watson has given way to WatsonX, and IBM is trying to ride the latest boom in AI. IBM is billing it as a development studio for companies to “train, tune and deploy” machine-learning models. Read More
Rick's Cafe AI 