Category robotics

Courtesy ChatGPT and Grammarly

Among ChatGPT’s myriad editorial skills is its ability to proofread your text at an extremely high level of proficiency.

And if all you’re looking for is an occasional proofread, you’ll find you can get help from ChatGPT — combined with similar AI tools — for free.

I began using ChatGPT as a back-up proofer for my primary proofreading tool — Grammarly — after I saw it consistently catching errors in text that Grammarly was missing.

Granted, the errors ChatGPT catches are generally minuscule (Grammarly really is an excellent proofreading tool, among its many other charms).

But sometimes, ChatGPT does catch outright misspellings that simply fly by Grammarly.

And on average, I find that ChatGPT spotlights about one-to-three errors that are missed by Grammarly per one thousand words of text.

One of the great beauties of creating a proofreading prompt for ChatGPT (a sample of one of mine follows) is that you can design it to do proofreading exactly as you prefer.

My proofer prompt, for example, instructs ChatGPT to retype the entire text it’s proofing, highlight each error it finds in bold, offer a suggested correction — and then explain its rationale for making each correction.

That may be overkill for some people.

But I prefer double-checking ChatGPT’s work myself and being given a sound reason for making a change — rather than simply trusting ChatGPT to ‘correct’ my text with no oversight.

I also greatly appreciate that I can add new rules to my ChatGPT proofer — or take some rules away — by simply changing a few words in the prompt.

And I really like the fact that my proofer grows more powerful with every upgrade of ChatGPT’s software.

For example: The ChatGPT proofer I use most (below) is more powerful and more meticulous in its proofreading when used with the most advanced version of ChatGPT — ChatGPT 4o — as compared to its use with previous versions of ChatGPT.

As with many things ChatGPT, your success designing a proofer hinges mightily on the precise wording of your prompt.

Sure, you can design a proofer with something simple like: “You are an expert proofreader. Please proofread the following text and highlight the errors in bold.”

But I’ve had better luck using a longer prompt that spells out — in excruciating detail — exactly what I’m looking for.

For example: In addition to asking for an error scan, I also ask ChatGPT to be meticulous as it’s scanning, to focus intensely on its task, to get extremely granular in its inspection (such as identifying correct placement of periods) and similar.

But simultaneously, I’m also careful not to overload ChatGPT with too many different kinds of requests in a single prompt — which can needlessly slow down ChatGPT, or even confuse it entirely.

As previously indicated, if you’re only looking to do some occasional proofreading, you can do so for free using ChatGPT and other tools and still enjoy a high level of performance.

For example: You can sign-up for Grammarly’s free version, which will do a basic, highly effective proofread of your text at absolutely no charge.

And then you can head over to ChatGPT, where you can double-check Grammarly’s work using free, limited access to ChatGPT’s most advanced AI engine, ChatGPT 4o.

Granted, you can only input about 15 prompts every three hours using ChatGPT-4o’s free version.

But if you only have a few documents to double-check for proofing, you’re all set.

For more extended, free proofing, you can also use Grammarly in combination with Gemini Advanced — Google’s direct competitor to ChatGPT-4o.

The reason: Gemini Advanced is based on the same genre of AI technology that powers ChatGPT. So a prompt developed for use with ChatGPT will also work flawlessly with Gemini Advanced.

Plus, Gemini Advanced currently offers an extremely generous, two-month free trial.

So chances are, you can theoretically proof an entire book if you so desired — over time — just using Grammarly’s free version, in concert with the Google Gemini Advanced’s free trial.

Another bonus: Given that the lion’s share of AI writers/tools on the market right now use the same genre of AI technology as ChatGPT and Gemini Advanced, you can also use any prompt initially developed for ChatGPT in any other AI tool based on the same genre of AI tech, including:

Jasper

Sudowrite

Anyword

INK

Scalenut

Neuraltext

Writesonic

Wordtune

Sapling

Notion Labs

Copy.ai

Rytr

Chibi AI

Surfer

Article Forge

WordAI

AI Writer

Hypotenuse AI

Longshot

CreaitorAI

CopySmith

OpenAI

Writer

GrowthBar

Closerscopy

ParagraphAI

Frase

A final tip before we take a look at a sample proofer: It’s always best to design your proofer as a stand-alone prompt — followed by a second prompt that you use to actually input the text you want proofed.

This technique ensures that you’re not giving ChatGPT too many words and/or too much data to process in any one prompt.

Even better: Inputting your text in a second prompt also expands the number of words ChatGPT will proofread for you, given that ChatGPT can only process and understand so many words in any given prompt.

In any event, here’s one of the homespun proofers I use when I’m proofing with Grammarly and I’m looking for ChatGPT to do an extremely granular double-check of Grammarly’s work:

Joe Dysart’s Proofer Prompt:

[You are a seasoned, award-winning expert in proofreading. Please conduct a meticulous, line-by-line proofread of text that I will provide you in the next prompt.

Focus intensely on the following aspects:

*Technical Accuracy: Identify and correct errors in spelling, grammar, punctuation, capitalization and formatting.

*Other Technical Errors: Identify and correct other technical errors not specifically listed in this prompt.

*Correct Placement of Periods and Quotes: Pay special attention to the placement of periods and quotes. Identify and correct any incorrect placement of periods and quotes and incorrect spacing associated with them.

*Consistency: Identify and correct inconsistent use of terminology, names, spelling, formatting and internal style rules (if applicable).

*Specific Conventions: Verify that the following conventions are employed:

~Allow the use of slang
~Allow the use of sentence fragments
~Allow the use of sentences that start with And
~Allow the use of sentences that start with But

To report the errors you find:

*Preserve Original: Retype the entire text with your changes.

*Highlight Errors: Highlight each error you find in bold.

*Provide Correction: Offer your correction for each error in parentheses directly after the bolded error.

*Explain Correction: For each correction you make using boldface type, please explain the correction, also in boldface type, using the format in the following example, which is delineated by three quote symbols “””solider (soldier) — The word soldier was misspelled.”””

*Always keep in mind your overarching goal: Your overarching goal is to provide the most comprehensive, meticulous proofreading of the text as possible.

Please indicate that you fully understand these proofreading instructions and have stored the instructions with the statement: I fully understand these proofreading instructions and have stored the instructions. Please input the text you’d like proofread with your next prompt using the words, “Here’s the text to proofread:”]

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

The post Free AI-Powered Proofreading appeared first on Robot Writers AI.

A combined team of roboticists from Stanford University and the Toyota Research Institute has found that adding audio data to visual data when training robots helps to improve their learning skills. The team has posted their research on the arXiv preprint server.

It resembles a malevolent robot from 1980s sci-fi but West Japan Railway's new humanoid employee was designed with nothing more sinister than a spot of painting and gardening in mind.

Researchers tested phononic nanomaterials designed with an automated genetic algorithm that responded to light pulses with controlled vibrations. This work may help in the development of next-generation sensors and computer devices.

Without any external input to guide its actions or decisions, a robot would behave like a machine, performing tasks without adaptation or autonomy. Serving as the critical link between the robot and its environment, sensors enable the robot to perceive and interpret.

“In the new future, every single interaction with the digital world will be through an AI assistant of some kind. We will be talking to these AI assistants all the time. Our entire digital diet will be mediated by AI systems,” Meta’s Chief AI Scientist Yann LeCun said at a recent Meta event. This bold prediction underscores a transformative shift in how we engage with technology, hinting at a future where AI personal assistants become indispensable in our daily lives.

LeCun’s vision is echoed across the tech industry. Demis Hassabis, CEO of Google DeepMind, emphasized their commitment to developing a universal agent for everyday life. He pointed out that this vision is the driving force behind Gemini, an AI designed to be multimodal from inception, capable of handling a diverse range of tasks and interactions.

These perspectives illustrate a consensus among leading AI researchers and developers: we are on the cusp of an era where AI personal assistants will significantly enhance both our personal and professional lives. Comparable to Tony Stark’s JARVIS, these AI systems are envisioned to seamlessly integrate into our routines, offering assistance and enhancing productivity in ways that were once the realm of science fiction.

However, to gauge our progress towards this ambitious goal, it is essential to first delineate what we expect from an AI personal assistant. Understanding these expectations provides a benchmark for evaluating current advancements and identifying areas that require further innovation.

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What We Expect from AI Personal Assistants

While certain features of an AI personal assistant might carry more weight than others, the following aspects form the foundation of an effective and useful assistant:

Intelligence and Accuracy. An AI personal assistant must be capable of delivering precise and reliable information, drawing from high-quality, credible sources. The assistant’s ability to comprehend and accurately respond to complex queries is essential for its effectiveness.

Transparency and Reliability. One critical expectation is the AI’s ability to acknowledge its limitations. When it lacks the information or is uncertain about an answer, it must clearly communicate this to the user, instead of ‘hallucinating.’ Otherwise, it doesn’t make much sense to have an assistant whose responses you always need to verify.

Multimodal Functionality. A robust AI personal assistant should be multimodal, capable of processing and understanding text, code, images, videos, and audio. This versatility ensures it can handle a wide range of tasks and inputs, making it highly adaptable and useful in various contexts.

Voice Accessibility. An AI assistant should be easily accessible via voice commands. It should respond quickly and naturally, mirroring the pace and quality of human communication. This instant accessibility enhances convenience and efficiency.

Real-time Streaming. The assistant should be always-on, omnipresent, and available across multiple channels. Whether through smartphones, smart speakers, or other connected devices, the AI must provide real-time assistance whenever and wherever needed.

Self-learning Abilities. You want your assistant to know your specific routines and preferences, but it is impractical to define exhaustive rules for every potential interaction. Therefore, an AI personal assistant should possess self-learning capabilities, allowing it to adapt and improve through interactions with a specific user. This personalized learning helps the assistant become increasingly effective over time

Autonomous Actions. Beyond providing information, a valuable AI assistant should have the autonomy to take action when necessary. This could include various tasks like managing calendars, making reservations, or sending emails, thereby streamlining tasks and reducing the user’s workload.

Security and Privacy. In an era where data security is paramount, AI personal assistants must ensure robust security measures. Users need confidence that their interactions and data are protected, maintaining their privacy and safeguarding against potential breaches.

Progress and Current Innovations

So where are we now? We obviously don’t yet have AI personal assistants that meet all the above criteria. But there are some tools that introduced significant breakthroughs in this area. Not surprisingly, they come from leading AI tech companies.

OpenAI’s GPT-4o

This May, OpenAI introduced their new flagship model, GPT-4o (“o” for “omni”). It marks a significant step towards more natural human-computer interaction. The model accepts input in any combination of text, audio, image, and video, and it can generate outputs in text, audio, and image formats. This multimodal capability positions GPT-4o as a versatile assistant for a variety of tasks.

Crucially, GPT-4o can be easily accessed via voice commands, supporting natural conversations with an impressive response time averaging 320 milliseconds, comparable to human interaction speeds. This accessibility and speed make it a strong candidate for real-time assistance in everyday scenarios.

In terms of intelligence, GPT-4o matches or exceeds the performance of GPT-4 Turbo, which currently leads many benchmarks. However, like other large language models, it remains prone to mistakes and hallucinations, limiting its use in tasks where accuracy is paramount. Despite these limitations, GPT-4o includes self-learning features, allowing it to improve responses based on user feedback. This partial self-learning ability helps it adapt to user preferences over time, though it is not yet as advanced as the personalized assistance envisioned in a JARVIS-like system.

While GPT-4o offers enhanced interaction capabilities, it does not perform autonomous tasks. Moreover, privacy remains a significant concern, as with many AI-powered tools, underscoring the need for robust security measures to protect user data.

Finally, OpenAI has not yet released GPT-4o with all the multimodal capabilities showcased in their demo videos. Currently, the public can only access the model with text and image inputs, and text outputs. Real-world testing of the model may uncover additional weaknesses.

Google’s Astra

Announced just a day after OpenAI’s GPT-4o, Google DeepMind’s Astra represents another significant leap in AI personal assistant technology. Astra responds to audio and video inputs in real time, much like GPT-4o, promising seamless interaction and immediate assistance.

The demo showcased Astra’s impressive capabilities: it could explain the functionality of a piece of code simply by observing someone’s screen through a smartphone camera, recognize a neighborhood by viewing the scenery from a window, and even “remember” the location of an object shown earlier in the video stream. Notably, part of the demo featured a user employing smart glasses instead of a phone, highlighting the potential for more integrated and innovative user experiences.

However, this remains an announcement, and the public does not yet have access to Astra. Thus, its real-world capabilities are still to be tested. It is likely that Astra, like other AI models, will still be prone to hallucinations and does not yet perform autonomous tasks. Nevertheless, the Google DeepMind team behind Astra has expressed a vision of developing a universal agent useful in everyday life, which suggests future iterations may include autonomous task performance.

Other Promising Players

As the race to develop advanced AI personal assistants heats up, several other major tech companies are making strategic moves, hinting at their imminent entries into this competitive arena. Although their next-generation AI personal assistants are yet to be launched, recent developments indicate significant progress.

Microsoft

Earlier this year, Microsoft acqui-hired Inflection, the company focused on developing “Pi, your personal AI.” While technically not an acquisition, Microsoft hired key staff members, including Mustafa Suleyman and Karen Simonyan, and paid approximately $650 million, mostly in the form of a licensing deal that makes Inflection’s models available for sale on the software giant’s Azure cloud service. Considering Mustafa Suleyman’s strong belief in personal artificial intelligence, this might be an indication that Microsoft is likely to offer its own personal AI assistant in the near future.

Amazon

Amazon, a pioneer in the voice assistant market with Alexa, remains committed to its mission of making Alexa “the world’s best personal assistant.” Recently, Amazon executed a strategy similar to Microsoft’s by hiring the co-founders and key employees of Adept AI, a startup known for developing AI-powered agents. The technology developed by Adept AI was licensed to Amazon, with the team joining Amazon’s AGI division to build real-world digital agents. Whether Amazon’s new product will cater primarily to enterprise customers or also introduce a personal AI assistant remains to be seen. However, integrating this technology could finally transform Alexa into a more powerful, conversational LLM-powered assistant. Currently, the old Alexa is hindering progress as Amazon has not yet figured out how to integrate the existing Alexa capabilities with the more advanced, conversational features touted for the new Alexa last fall.

Apple

Another leader in voice assistants, Apple, is also busy improving Siri. The company is partnering with OpenAI to power some of its AI features with ChatGPT technology, while also building its own models. Apple’s published research indicates a focus on small and efficient models, aiming to have all AI features running on-device, fully offline. Apple is also working on making the new AI-powered Siri more conversational and versatile, allowing users to control their apps with voice commands. For example, users will be able to ask the voice assistant to find information inside a particular email or even surface a photo of a specific friend. Apple places a strong emphasis on security, with the system automatically deciding whether to use on-device processing or contact Apple’s private cloud computing server to fulfill requests.

These strategic moves by Microsoft, Amazon, and Apple reflect a broader trend towards more sophisticated, user-friendly AI personal assistants. As these companies continue to innovate and develop their technologies, we can anticipate significant advancements in the capabilities and functionalities of AI personal assistants in the near future.

The Road Ahead

The race to develop the next generation of AI personal assistants is intensifying, with major tech companies like OpenAI, Google, Microsoft, Amazon, and Apple making significant strides. Each of these players brings unique innovations and perspectives, pushing the boundaries of what AI can achieve in our daily lives. While we are not yet at the point where AI personal assistants meet all the ideal criteria, the advancements we see today are promising steps toward a future where these digital companions become an integral part of our personal and professional lives. As the technology continues to evolve, the vision of having a truly intelligent, multimodal, and autonomous AI assistant appears closer than ever.

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The post Next-Gen AI Assistants: Innovations from OpenAI, Google, and Beyond appeared first on TOPBOTS.

Medical technology relies on FAULHABER not only in robot-supported procedures. For example, drive systems are used in implantable heart pumps, surgical hand tools, in ophthalmology, in cosmetics and in medical imaging and image processing.

With a new surgical intervention and neuroprosthetic interface, researchers restored a natural walking gait in people with amputations below the knee. Seven patients were able to walk faster, avoid obstacles, and climb stairs more naturally than people with a traditional amputation.

Computer scientists have invented a camera mechanism that improves how robots see and react to the world around them. Inspired by how the human eye works, their innovative camera system mimics the tiny involuntary movements used by the eye to maintain clear and stable vision over time.

As an undergraduate engineering student in Delhi, India, Amisha Bhaskar took a field trip to a facility for disabled war veterans and met a man who had lost both hands. When she asked him what technologies could improve his life, his reply left an indelible impression: He wanted something so he could take care of himself and not be forced to rely upon others.

A team led by University of Maryland computer scientists has invented a camera mechanism that improves how robots see and react to the world around them. Inspired by how the human eye works, their innovative camera system mimics the tiny involuntary movements used by the eye to maintain clear and stable vision over time.

Researchers have developed nanorobots that kill cancer cells in mice. The robot's weapon is hidden in a nanostructure and is exposed only in the tumour microenvironment, sparing healthy cells.

Researchers have developed a lightweight fluidic engine to power muscle-mimicking soft robots for use in assistive devices. What sets the new engine apart is its ability to generate significant force without being tethered to an external power source.

While the current focus is on strawberries, the system is designed to be scalable and adaptable to other crops, such as tomatoes or peppers, offering a versatile solution for farmers.

A slew of major stories in AI writing that broke in Q2 have made the future for writers and editors crystal clear: The wholesale transition of writing-by-humans to writing-by-AI-machines has begun.

Fading are the days when publishers and AI evangelists hid behind the euphemism that AI writers are just Silicon buddies looking to shoulder the drudge work so their human counterparts can do more interesting work.

And in their place are increasingly candid, bald admissions — or unquestionable evidence of the same — of a common-sense reality that anyone paying close attention to AI has known for years.

Specifically: If words are your stock-in-trade and AI-powered machines can do your kind of writing much faster — and much more inexpensively — it makes no sense to keep you employed.

A few examples of that new reality from Q2:

~Sam Altman, CEO of ChatGPT-maker OpenAI, predicts that AI will ultimately usurp 95% of all marketing work currently performed by agencies, strategists and creatives

~The BBC reports that a publisher reduced its writing and editorial staff from 60+ to a single, lone editor — simply by switching to AI

~A Swedish financial company reduced its marketing costs by $10 million, simply by funneling that marketing work to AI rather than to outside, human creatives

~WPP — the world’s largest ad agency — cut a deal to bring in Google Gemini, a ChatGPT competitor, to help write ad scripts, auto-create narration and auto-generate product images

~Newsweek announced it’s all-in on AI and has plans to integrate the tech into the magazine’s operations as deeply as possible

Granted, news editors and reporters still have some cover, given that AI in many instances still does not have the trust and sources to unearth new data from the world — and then work that new information into news stories.

But for writers in marketing, copywriting and similar jobs who are playing around with ideas and concepts — but not bringing fresh data to their audiences — there is only one recourse: They need to get smart, very quickly, on how to best leverage AI writing tools in their day-to-day work.

And once they’re up-to-speed, they need to engage with that AI knowing that like the 60+ copywriting shop that was shrunken down to a single editor by AI, they still may be out-the-door — no matter how sophisticated their AI smarts.

Here’s detail on the wholesale migration, along with other key stories that shaped the growing impact of AI writing in Q2:

*ChatGPT CEO: AI Will Usurp 95% of Marketing Work: In a stunning moment of candor, ChatGPT CEO Sam Altman has stated that AI will usurp 95% of all the marketing work currently performed by agencies, strategists and creatives.

Altman’s prediction can be found in a new book — offered by subscription — “Our AI Journey,” by Adam Brotman and Andy Sack.

Observes Mike Kaput, chief content officer, Marketing AI Institute, in reaction to Altman’s reported prediction: “To say it blew us away is an understatement.”

Altman’s exact words, according to Brotman and Sack, were: “95% of what marketers use agencies, strategists, and creative professionals for today will easily, nearly instantly and at almost no cost be handled by the AI.

“And the AI will likely be able to test the creative against real or synthetic customer focus groups for predicting results and optimizing.

“Again — all free, instant and nearly perfect. Images, videos, campaign ideas? No problem.”

For more on Altman’s revelation, check out this riveting article by Kaput.

Keep on rockin’ in the free world.

*The Myth of the ‘Cheery, AI Collaborator’: AI Reduces 60+ Copywriting Team to One Editor: In yet another bone-chilling example of how AI is hollowing-out copywriting teams, this BBC report details how AI turned a 60+ copywriting team into a one-man operation.

First introduced by the publisher in 2023, AI slowly began to usurp more and more jobs until by 2024, everyone on the team was vaporized save for one, lone editor.

Observes the last of the team, who chooses to remain anonymous: “All of a sudden, I was just doing everyone’s job.

“Mostly, it was just about cleaning things up and making the writing sound less awkward, cutting-out weirdly formal or over-enthusiastic language.

“It was more editing than I had to do with human writers, but it was always the exact same kinds of edits. The real problem was it was just so repetitive and boring. It started to feel like I was the robot.”

That account is a long way from current-day AI evangelism, which insists AI is little more than a warm-and-fuzzy friend who will always help you — and never hurt.

For editors and writers who are not tasked with unearthing fresh news data in their jobs, the message is clear: Increasingly, staying alive in copyediting has become a fight to be ‘the last one standing.’

*Pink Slip Heaven: Scores of Jobs Go Bye-Bye as Marketing Department Embraces AI: Remember that cheerful AI assistant and ‘collaborator’ that was going to free-up your days so you could indulge in much more meaningful work?

It just took your job.

Writer Megan Graham reports that $10 million worth of marketing work that would have gone to content creators for a Swedish financial company is now handled by AI.

Observes Graham: “Using generative AI tools such as Midjourney and DALL-E saved the company $1.5 million on image production costs in the first quarter — while slashing its image development timeline to seven days from six weeks.

“Klarna also said it had decreased by 25% its spending on external marketing suppliers (code-phrase for editors, writers and graphic artists) for tasks such as social media, translation and production.”

*Newsweek Goes Full AI: Reporters That Boot-up in Seconds: Brushing aside fears of editorial job loss, Newsweek has fully embraced AI and is looking to integrate the tech as deeply as possible into the magazine’s operations.

Says Jennifer Cunningham, executive editor, Newsweek: “I think that the difference between newsrooms that embrace AI and newsrooms that shun AI is really going to prove itself over the next several months and years.

“We have really embraced AI as an opportunity — and not some sort of boogeyman that’s lurking in the newsroom.”

We’ll see.

*Dreams Of AI Mojo: World’s Largest Ad Agency Partners With Google: In a head-turning move, WPP — parent company of some of the biggest agencies in advertising — has reached-out to Google for AI enhancement.

Specifically, the company is looking to integrate Google’s Gemini AI into its services to auto-write ad scripts, automate ad narration and auto-generate product images.

Observes Stephan Pretorious, Chief Technology Officer, WPP: “I believe this will be a game-changer for our clients and the marketing industry at large.”

*AI Now Crafts Fictional Characters While You Nap: AI pioneer Sudowrite is promising a new module writers can use to auto-build personality traits, background, physical appearances and mannerisms for fictional characters.

Also promised is a new world-building tool that will enable writers to auto-design fictional worlds ranging from dystopian cities to magical realms.

The AI tool — which uses AI engines like GPT-4 and Claude 3 to work its magic — will also be enhanced system-wide to enable writers to auto-generate fiction more efficiently.

*Apple Goes All In on ChatGPT: It’s official: One of the world’s richest and mightiest tech companies has turned to ChatGPT to bring AI to its smartphone.

A major coup for ChatGPT’s maker OpenAI, the deal will bring ChatGPT to millions of iPhone users who are running — or will be running — iOS 18 software on their devices.

The Times of India also reports that Apple may feature ChatGPT competitors on its iPhone as well — such as Google Gemini.

But so far, no such deals have been inked.

*Thousands of Free, ChatGPT Competitors Pop-Up on the Web: Thousands of free, alternative versions of a new AI engine released by Mark Zuckerberg of Facebook fame are popping-up on the Web.

The reason: Zuckerberg released his new AI engine — dubbed Llama 3 –as free, open source code that can be downloaded and altered by anyone interested in doing a little tinkering.

This is great news for consumers, given that thousands upon thousands of AI pros are coming up with competitive — and free — AI alternatives to proprietary AI solutions like ChatGPT.

That forces market leaders like OpenAI — the maker of ChatGPT — to continually develop ever-more-sophisticated versions of their tech.

And it makes it much tougher for OpenAI and similar proprietary companies to raise prices aggressively when thousands of free alternatives abound.

*Less Popular Than Your Average Cat Video: Only 23% of U.S. Adults Have Tried ChatGPT: Nearly a year-and-a-half since ChatGPT first stunned the world, only 23% of U.S. adults have actually used it, according to a new study from Pew.

For many who track the tech closely — and see the emergence of ChatGPT and similar AI as a pivotal moment in the history of humanity — the meager adoption rate is tough to understand.

Not surprisingly, young adults under 30 are most enthusiastic about ChatGPT — 43% have tried the AI.

Oldest adults, 65-and-up, are least interested in the tech — only 6% have tried the tool, according to Pew.

*AI Smarter Than Many Humans By 2027?: If it feels like we’re all living in a sci-fi movie that’s ready to careen off a cliff into AI oblivion, don’t blame Leopold Aschenbrenner.

His firsthand take on the potential devastation ahead — courtesy of AI — leaves him no choice but to sound the alarm.

A former researcher for OpenAI — maker of ChatGPT — Aschenbrenner warns that AI is moving so fast, we could see AI that’s as smart as an AI engineer by 2027.

Even more head-turning: Once AI is operating at that intellectual level, it’s just another jump or two — perhaps another few years — until we literally have “many millions” of virtual AI entities that have taken over the ever-increasing sophistication of AI, Aschenbrenner says.

Observes Aschenbrenner: “Rather than a few hundred researchers and engineers at a leading AI lab, we’d have more than one hundred thousand times that—(AI agents) furiously working on algorithmic breakthroughs, day and night.

“Before we know it, we would have super-intelligence on our hands — AI systems vastly smarter than humans, capable of novel, creative, complicated behavior we couldn’t even begin to understand.”

In essence, AI will have created its own digital civilization.

And it’s highly feasible that civilization would be populated by “several billions” of super-intelligent AI entities, according to Aschenbrenner.

The stomach-churning problem with that scenario: Given the human greed to possess such vast AI power unilaterally, it’s very likely that the U.S. could find itself in an all-or-nothing race with China to dominate AI.

Even worse: The U.S. could find itself in an all-out war with China to dominate AI.

Granted, it seems that for every in-the-know AI researcher like Aschenbrenner, there’s another equally qualified AI researcher who insists those fears are extremely overblown.

Yann LeCun, chief AI scientist at Meta — Facebook’s parent company — for example, believes that such AI gloom-and-doom nightmares are misguided and premature.

Even so, Aschenbrenner has staked his professional reputation on his assertions.

And he’s offered his complete analysis of what could be in a 156-page treatise entitled, “Situational Awareness: The Decade Ahead.”

(Gratefully, Aschenbrenner’s tome is rendered in a conversational, engaging and enthusiastic writing style.)

For close followers of AI who are looking to evaluate a definitive perspective on how our world could be completely transformed beyond our imaginations — within the next decade — Aschenbrenner’s treatise is a must-read.

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

The post Top Ten Stories in AI Writing, Q2 2024 appeared first on Robot Writers AI.