Category Archives: Artificial General Intelligence

SHANGHAI, April 20, 2023 /PRNewswire/ -- The Shanghai International Automobile Industry Exhibition ("Auto Shanghai 2023"), themed "Embracing the New Era of the Automotive Industry," has been held with a focus on the innovative changes in the automotive industry brought about by technology. SenseAuto, the Intelligent Vehicle Platform of SenseTime, made its third appearance at the exhibition with the three-in-one product suite of intelligent cabin, intelligent driving, and collaborative cloud, showcasing its full-stack intelligent driving solution and six new intelligent cabin products designed to create the future cabin experience with advanced perception capabilities. Additionally, nearly 30 models produced in collaboration with SenseAuto were unveiled at the exhibition, further emphasizing its industry-leading position.

SenseAuto made its third appearance at Auto Shanghai

At the Key Tech 2023 forum, Prof. Wang Xiaogang, Co-founder, Chief Scientist and President of Intelligent Automobile Group, SenseTime, delivered a keynote speech emphasizing that smart autos provide ideal scenarios for AGI (Artificial General Intelligence) to facilitate closed-loop interactions between intelligent driving and passenger experiences in the "third living space", which presents endless possibilities.

SenseAuto empowers nearly 30 mass-produced models showcased at Auto Shanghai 2023In 2022, SenseAuto Cabin and SenseAuto Pilot products were adapted and delivered to 27 vehicle models with more than 8 million new pipelines. These products now cover more than 80 car models from over 30 automotive companies, confirming SenseAuto's continued leadership in the industry.

In the field of intelligent driving, SenseAuto has established mass-production partnerships with leading automakers in China, such as GAC and Neta. At the exhibition, SenseAuto showcased the GAC AION LX Plus, which leverages SenseAuto's stable surround BEV (Bird 's-Eye-View) perception and powerful general target perception capabilities to create a comprehensive intelligent Navigated Driving Assist (NDA) that is capable of completing various challenging perception tasks. The Neta S, another exhibited model at the show, is also equipped with SenseAuto's full-stack intelligent driving solution which provides consumers with a reliable and efficient assisted driving experience in highway scenarios.

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In the field of intelligent cabin, SenseAuto is committed to developing the automotive industry's most influential AI empowered platform with the aim of providing extremely safe, interactive, and personalized experiences for users. The NIO ES7 model exhibited supports functions such as driver fatigue alerts, Face ID, and child presence detection. SenseAuto's cutting-edge visual AI technology has boosted the accuracy of driver attention detection by 53% in long-tail scenarios, and by 47% in complex scenarios involving users with narrow-set eyes, closed eyes, and backlighting.

The highly anticipated ZEEKR X model showcased features from SenseAuto's groundbreaking intelligent B-pillar interactive system, a first-of-its-kind innovation that allows for contactless unlocking and entry. Other models on display that boast SenseAuto's cutting-edge DMS (Driver Monitoring System) and OMS (Occupant Monitoring System) technologies include Dongfeng Mengshi 917, GAC's Trumpchi E9, Emkoo, as well as the M8 Master models. Moreover, HiPhi has collaborated with SenseAuto on multiple Smart Cabin features and Changan Yida is equipped with SenseAuto's health management product, which can detect various health indicators of passengers in just 30 seconds, elevating travel safety to new heights.

Six Innovative smart cabin features for an intelligent "third living space"SenseAuto is at the forefront of intelligent cabin innovations, with multi-model interaction that integrates vision, speech, and natural language understanding. SenseTime's newly launched "SenseNova" foundation model set, which introduces avariety of foundation models and capabilities in natural language processing and content generation, such as digital human, opens up numerous possibilities for the smart cabin as a "third living space".

SenseAuto presented a futuristic demo cabin at Auto Shanghai 2023, featuring an AI virtual assistant that welcomes guests and directs them to their seats. In addition, SenseTime's latest large-scale language model (LLM), "SenseChat", interacted with guests and provided personalized content recommendations. The "SenseMirage" text-to-image creation platform has also been integrated with the exhibition cabin for the first time. With the help of SenseTime's AIGC (AI-Generated Content) capabilities, guests can enjoy a fun-filled travel experience with various styles of photos generated for them.

At the exhibition, SenseAuto unveiled six industry-first features including Lip-Reading, Guard Mode, Intelligent Rescue, Air Touch, AR Karaoke and Intelligent Screensaver. With six years of industry experience, SenseAuto has accumulated to date a portfolio of 29 features, of which, over 10 are industry-firsts.

SenseNova accelerates mass-production of smart drivingSenseAuto is revolutionizing the autonomous driving industry with its full-stack intelligent driving solution, which integrates driving and parking. The innovative SenseAuto Pilot Entry is cost-effective solution that uses parking cameras for driving functions. SenseAuto's parking feature supports cross-layer parking lot routing, trajectory tracking, intelligent avoidance, and target parking functions to fulfill multiple parking needs in multi-level parking lots.

SenseNova has enabled SenseAuto to achieve the first domestic mass production of BEV perception and pioneer the automatic driving GOP perception system. SenseAuto is proactively driving innovation in the R&D ofautonomous driving technology, leveraging SenseTime's large model system. Its self-developed UniAD has become the industry's first perception and decision intelligence integrated end-to-end autonomous driving solution. The large model is also used for automated data annotation and product testing, which has increased the model iteration efficiency by hundreds of times.

SenseAuto's success is evident in its partnerships with over 30 automotive manufacturers and more than 50 ecosystem partners worldwide.With plans to bring its technology to over 31 million vehicles in the next few years, SenseAuto is leading the way in intelligent vehicle innovation. Leveraging the capabilities of SenseNova, SenseAuto is poised to continue riding the wave of AGI and enhancing its R&D efficiency and commercialization process towards a new era of human-vehicle collaborative driving.

About SenseTime: https://www.sensetime.com/en/about-index#1

About SenseAuto: https://www.sensetime.com/en/product-business?categoryId=1095&gioNav=1

(PRNewsfoto/SenseTime)

Cision

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SOURCE SenseTime

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SenseAuto Empowers Nearly 30 Mass-produced Models Exhibited at Auto Shanghai 2023 and Unveils Six Intelligent Cabin Products - Yahoo Finance

AI is able to pick up additional languages, doing so without magic or pixie dust.getty

The noted author Geoffrey Willans professed to say that anyone who knows no foreign language knows nothing of their own language.

Do you agree with that bold assertion?

Lets give the matter some serious thought.

First, perhaps we can agree that anyone that knows only one language could be labeled as being monolingual. Their native language is whatever language they have come to know. All other languages are said to be foreign to them, thus, if they opt to learn an additional language we could contend that they have picked up a foreign language.

Second, I assume we can concur that anyone that knows two languages could be given the lofty title of being bilingual. For those that know three or more languages, we will reserve the impressive label of being multilingual. An aspect that we might quibble about consists of how much of a language someone must know in order to be considered fluent enough in that language to count as intrepidly knowing an additional language. Hold onto that vexing question since well come back around to it later on herein.

Got a quick question for you.

How are you when it comes to being a language-wielding wizard?

You undoubtedly have friends or colleagues that speak a handful of languages, maybe you do likewise. The odds are that you are probably stronger in just one or two. The other languages are somewhat distant and sketchy in your mind. If push comes to shove, you can at least formulate fundamental sentences and likely comprehend those other languages to some slim degree.

The apex of the language gambit seems to be those amazing polyglots that know a dozen or dozens of languages. It seems nearly impossible to pull off. They imbue languages as easily as wearing a slew of socks and shoes. One moment conveying something elegant in one language and readily jumping over into a different language, nearly at the drop of a hat.

On social media, there are those polyglots that dazzle us by quickly shifting from language to language. They make videos in which they show the surprise and awe of others that admire their ability to effortlessly use a multitude of languages. You have surely wondered whether the polyglot was born with a special knack for languages or whether they truly had to learn many languages in the same way that you learned the two or three that you know. This is the classic question of whether language learning is more so nature versus nurture. We wont be solving that one herein.

There is an important reason that I bring up this weighty discussion overall about being able to use a multitude of languages.

Get yourself ready for the twist.

Maybe sit down and prepare for it.

The latest in generative AI such as ChatGPT and other such AI apps have seemingly been able to pick up additional languages beyond the one or ones that they appeared to have been initially data trained in. AI researchers and AI developers arent exactly sure why this is attainable. We will address the matter and seek to explore various postulated ways in which this can arise.

The topic has recently become a hot one due to an episode of the famed TV show 60 Minutes that interviewed Google executives. During the interviews, a Google exec stated that their AI app was able to engage in Bengali even though it was said to not have been data trained in that language. This enlisted a burst of AI hype, suggesting in this instance that the AI somehow magically made a choice to learn the additional language and proceeded to do so on its own.

Yikes, one might assume, this is surely a sign that these AI apps are converging toward being sentient. How else could the AI make the choice to learn another language and then follow up by learning it? That seems proof positive that contemporary AI is slipping and sliding toward Artificial General Intelligence (AGI), the moniker given to AI that can perform as humans do and otherwise be construed as possessing sentience.

It might be wise to take a deep breath and not fall for these wacky notions.

The amount of fearmongering and anthropomorphizing of AI that is going on right now is beyond the pale. Sadly, it is at times simply a means of garnering views. In other cases, the person or persons involved do not know what they are talking about, or they are being loosey-goosey for a variety of reasons.

In todays column, Id like to set the record straight and examine the matter of how generative AI such as ChatGPT and other AI apps might be able to pick up additional languages. The gist is that this can be mathematically and computationally explained. We dont need to refer to voodoo dolls or create false incantations to get there.

Logic and sensibility can prevail.

Vital Background About Generative AI

Before I get further into this topic, Id like to make sure we are all on the same page overall about what generative AI is and also what ChatGPT and its successor GPT-4 are all about. For my ongoing coverage of generative AI and the latest twists and turns, see the link here.

If you are already versed in generative AI such as ChatGPT, you can skim through this foundational portion or possibly even skip ahead to the next section of this discussion. You decide what suits your background and experience.

Im sure that you already know that ChatGPT is a headline-grabbing AI app devised by AI maker OpenAI that can produce fluent essays and carry on interactive dialogues, almost as though being undertaken by human hands. A person enters a written prompt, ChatGPT responds with a few sentences or an entire essay, and the resulting encounter seems eerily as though another person is chatting with you rather than an AI application. This type of AI is classified as generative AI due to generating or producing its outputs. ChatGPT is a text-to-text generative AI app that takes text as input and produces text as output. I prefer to refer to this as text-to-essay since the outputs are usually of an essay style.

Please know though that this AI and indeed no other AI is currently sentient. Generative AI is based on a complex computational algorithm that has been data trained on text from the Internet and admittedly can do some quite impressive pattern-matching to be able to perform a mathematical mimicry of human wording and natural language. To know more about how ChatGPT works, see my explanation at the link here. If you are interested in the successor to ChatGPT, coined GPT-4, see the discussion at the link here.

There are four primary modes of being able to access or utilize ChatGPT:

The capability of being able to develop your own app and connect it to ChatGPT is quite significant. On top of that capability comes the addition of being able to craft plugins for ChatGPT. The use of plugins means that when people are using ChatGPT, they can potentially invoke your app easily and seamlessly.

I and others are saying that this will give rise to ChatGPT as a platform.

All manner of new apps and existing apps are going to hurriedly connect with ChatGPT. Doing so provides the interactive conversational functionality of ChatGPT. The users of your app will be impressed with the added facility. You will likely get a bevy of new users for your app. Furthermore, if you also provide an approved plugin, this means that anyone using ChatGPT can now make use of your app. This could demonstrably expand your audience of potential users.

The temptation to have your app connect with ChatGPT is through the roof. Even if you dont create an app, you still might be thinking of encouraging your customers or clients to use ChatGPT in conjunction with your everyday services. The problem though is that if they encroach onto banned uses, their own accounts on ChatGPT will also face scrutiny and potentially be locked out by OpenAI.

As noted, generative AI is pre-trained and makes use of a complex mathematical and computational formulation that has been set up by examining patterns in written words and stories across the web. As a result of examining thousands and millions of written passages, the AI can spew out new essays and stories that are a mishmash of what was found. By adding in various probabilistic functionality, the resulting text is pretty much unique in comparison to what has been used in the training set.

There are numerous concerns about generative AI.

One crucial downside is that the essays produced by a generative-based AI app can have various falsehoods embedded, including manifestly untrue facts, facts that are misleadingly portrayed, and apparent facts that are entirely fabricated. Those fabricated aspects are often referred to as a form of AI hallucinations, a catchphrase that I disfavor but lamentedly seems to be gaining popular traction anyway (for my detailed explanation about why this is lousy and unsuitable terminology, see my coverage at the link here).

Another concern is that humans can readily take credit for a generative AI-produced essay, despite not having composed the essay themselves. You might have heard that teachers and schools are quite concerned about the emergence of generative AI apps. Students can potentially use generative AI to write their assigned essays. If a student claims that an essay was written by their own hand, there is little chance of the teacher being able to discern whether it was instead forged by generative AI. For my analysis of this student and teacher confounding facet, see my coverage at the link here and the link here.

There have been some zany outsized claims on social media about Generative AI asserting that this latest version of AI is in fact sentient AI (nope, they are wrong!). Those in AI Ethics and AI Law are notably worried about this burgeoning trend of outstretched claims. You might politely say that some people are overstating what todays AI can do. They assume that AI has capabilities that we havent yet been able to achieve. Thats unfortunate. Worse still, they can allow themselves and others to get into dire situations because of an assumption that the AI will be sentient or human-like in being able to take action.

Do not anthropomorphize AI.

Doing so will get you caught in a sticky and dour reliance trap of expecting the AI to do things it is unable to perform. With that being said, the latest in generative AI is relatively impressive for what it can do. Be aware though that there are significant limitations that you ought to continually keep in mind when using any generative AI app.

One final forewarning for now.

Whatever you see or read in a generative AI response that seems to be conveyed as purely factual (dates, places, people, etc.), make sure to remain skeptical and be willing to double-check what you see.

Yes, dates can be concocted, places can be made up, and elements that we usually expect to be above reproach are all subject to suspicions. Do not believe what you read and keep a skeptical eye when examining any generative AI essays or outputs. If a generative AI app tells you that President Abraham Lincoln flew around the country in a private jet, you would undoubtedly know that this is malarky. Unfortunately, some people might not realize that jets werent around in his day, or they might know but fail to notice that the essay makes this brazen and outrageously false claim.

A strong dose of healthy skepticism and a persistent mindset of disbelief will be your best asset when using generative AI.

Into all of this comes a slew of AI Ethics and AI Law considerations.

There are ongoing efforts to imbue Ethical AI principles into the development and fielding of AI apps. A growing contingent of concerned and erstwhile AI ethicists are trying to ensure that efforts to devise and adopt AI takes into account a view of doing AI For Good and averting AI For Bad. Likewise, there are proposed new AI laws that are being bandied around as potential solutions to keep AI endeavors from going amok on human rights and the like. For my ongoing and extensive coverage of AI Ethics and AI Law, see the link here and the link here, just to name a few.

The development and promulgation of Ethical AI precepts are being pursued to hopefully prevent society from falling into a myriad of AI-inducing traps. For my coverage of the UN AI Ethics principles as devised and supported by nearly 200 countries via the efforts of UNESCO, see the link here. In a similar vein, new AI laws are being explored to try and keep AI on an even keel. One of the latest takes consists of a set of proposed AI Bill of Rights that the U.S. White House recently released to identify human rights in an age of AI, see the link here. It takes a village to keep AI and AI developers on a rightful path and deter the purposeful or accidental underhanded efforts that might undercut society.

Ill be interweaving AI Ethics and AI Law related considerations into this discussion.

Figuring Out The Languages Conundrum

We are ready to further unpack this thorny matter.

I would like to start by discussing how humans seem to learn languages. I do so cautiously in the sense that I am not at all going to suggest or imply that todays AI is doing anything of the same. As earlier stated, it is a misguided and misleading endeavor to associate the human mind with the mathematical and computational realm of contemporary AI.

Nonetheless, some overarching reveals might be useful to note.

We shall begin by considering the use case of humans that know only one language, ergo being monolingual. If you know only one language, there is an interesting argument to be made that you might be able to learn a second language when undergoing persistent exposure to that second language.

Consider for example this excerpt from a research study entitled English Only? Monolinguals In Linguistically Diverse Contexts Have An Edge In Language Learning by researchers Kinsey Bice and Judith Kroll:

The crux is that your awareness of a single language can be potentially leveraged toward learning a second language by mere immersion into that second language. This is described as arising when in a linguistically diverse context. You might not necessarily grasp what those words in the other language mean, but you kind of catch on by exposure to the language and presumably due to your already mindful familiarity with your primary language.

Note that you didnt particularly have to be told how the second language works.

Of course, most people take a class that entails learning a second language and are given explicit instruction. That likely is the prudent path. The other possibility is that via a semblance of mental osmosis or mental gymnastics, you can gradually glean a second language. We can make a reasonable assumption that this is due to already knowing one language. If you didnt know any language at all, presumably you wouldnt have the mental formulation that could so readily pattern onto a second language. You would be starting from a veritable blank slate (well, maybe, since there is debate over what our brains consist of about wired versus learned aspects of language as a default).

This then covers a vital aspect that when you know one language, you possibly do not need explicit teaching about another language to learn that second language. We seem to be able to use a sense of language structure and patterns to figure out a second language. Not everyone can easily do so. It might be that you would struggle mightily over a lengthy period of time to comprehend the second language. A faster path would usually consist of explicit instruction.

But anyway, we can at times make that mental leap.

Lets explore another angle to this.

There is an intriguing postulation that if you learn a second language as a child, the result is that you will be more amenable to learning additional languages as an adult. Those people that are only versed in a single language throughout childhood allegedly will have a harder time learning a second language as an adult.

Consider this excerpt from a research study entitled A Critical Period For Second Language Acquisition: Evidence From 2/3 Million English Speakers by researchers Joshua Hartshorne, Joshua Tenenbaum, and Steven Pinker:

In short, a common suspected phenomenon is that a child that learns only one language during childhood is not somehow formulating a broadened capacity for learning languages all told. If they learn at least a second language, in theory, this is enabling their mind to discern how languages contrast and compare. In turn, this is setting them up for being more versed in that second language than would an adult that learns the second language while an adult. Plus, the child is somewhat prepared to learn a third language or additional languages throughout childhood and as an adult.

The idea too is that an adult that only learned one language as a child has settled into a one-language mode. They havent had to stretch their mind to cope with a second language. Thus, even though as an adult they should be able to presumably learn a second language, they might have difficulty doing so because they had not previously formulated the mentally beneficial generic structures and patterns to tackle a second language.

Please know that there is a great deal of controversy associated with those notions. Some agree with those points, some do not. Furthermore, the explanations for why this does occur, assuming it does occur, vary quite a bit.

If you want a boatload of controversy, heres more such speculation that gets a lot of heated discourse on this topic. Hold onto your hat.

Consider this excerpt from a research study entitled The Benefits Of Multilingualism To The Personal And Professional Development Of Residents Of The US by Judith Kroll and Paola Dussias:

The contention is that individuals with exposure to multiple languages during childhood benefit in many ways including greater openness to other languages and new learning itself.

Life though is not always a bed of roses. A concern is that a child might get confused or confounded when trying to learn more than one language during their childhood. The claim is that a child might not be able to focus on their considered primary language. They could inadvertently mix the other language and end up in a nowhere zone. They arent able to pinpoint their main language, and nor are they able to pinpoint the second language.

Parents are presented with a tough choice. Do you proceed to have your child learn a second language, doing so under the hopes and belief that this is the best means of aiding your child toward language learning and perhaps other advantages of mental stimulation? Or do you focus on one language alone, believing that once they are older it might be better to have them then attempt a second language, rather than doing so as a child?

Much of our existing educational system has landed on the side that knowing a second language as a child seems to be the more prudent option. Schools typically require a minimum amount of second language learning during elementary school, and ramp this up in high school. Colleges tend to do so as well.

Returning to the cited study above, heres what the researchers further state:

The expression often used is that when you know two or more languages, you have formulated a mental juggling capacity that allows you to switch from language to language. To some extent, the two or more languages might be construed as mental competitors, fighting against each other to win in your mental contortions when interpreting language. Some people relish this. Some people have a hard time with it.

I think that covers enough of the vast topic of language learning for the purposes herein. As mentioned, the language arena is complex and a longstanding matter that continues to be bandied around. Numerous theories exist. It is a fascinating topic and one that obviously is of extreme significance to humankind due to our reliance on language.

Imagine what our lives would be like if we had no language to communicate with. Be thankful for our wonderous language capacities, no matter how they seem to arise.

Generative AI And The Languages Affair

We are now in a position to ease into the big question about generative AI such as ChatGPT and the use of languages.

AI researcher Jan Leike at OpenAI tweeted this intriguing question on February 13, 2023:

And within the InstructGPT research paper that was being referred to, this point is made about the languages in the dataset that was used:

This brings us to my list of precepts about generative AI and the pattern-matching associated with languages, specifically:

A quick unpacking might be helpful.

First, realize that words are considered to be objects by most generative AI setups.

As Ive discussed about ChatGPT and GPT-4, see the link here, text or words are divided up into tokens that are approximately 3 letters or so in length. These tokens are various assigned numbers. The numbers are used to do the pattern matching amidst the plethora of words that are for example scanned during the data training of the generative AI. All of it is tokenized and used in a numeric format.

The text you enter as a prompt is encoded into a tokenized number. The response formulated by generative AI is a series of tokenized numbers that are then mapped into the corresponding letters and word segments for presentation to you when using an AI app.

The words being scanned during data training are typically sourced on the Internet in terms of passages of text that are posted on websites. Only a tiny fraction of the text on the Internet is usually involved in this scanning for data training and pattern-matching formulation purposes. A mathematical and computational network structure is devised that attempts to statistically associate words with other words, based on how humans use words and as exhibited via the Internet sites being scanned.

You might find of interest that there are concerns that this widespread text scanning is possibly violating Intellectual Property (IP) rights and entails plagiarism, see my analysis at the link here. It is an issue being pursued in our courts and well need to wait and see how the courts rule on this.

By and large, the generative AI that you hear about is data trained on words from the Internet that are in English, including for example the data training of ChatGPT. Though the bulk of the words encountered during the Internet scanning was in English, there is nonetheless some amount of foreign or other language words that are also likely to be encountered. This could be by purposeful design as guided by the AI developers, but usually, it is more likely a happenstance as to the casting of a shall we say a rather wide net when sauntering across a swath of the Internet.

It is like aiming to catch fish in your fishnet and meanwhile, you just so happen to also get some lobsters, crabs, and other entities along the way.

What happens with those other entities that are caught in the fishnet?

One possibility is that the pattern matching of the generative AI opts to treat those encountered words as a separate category in comparison to the English words being examined. They are outliers in contrast to the preponderance of words being patterned on. In a sense, each such identification of foreign words can be classified as belonging to a different potential language. Per my analogy, if fish were being scanned, the appearance of a lobster or a crab would be quite different, and ergo could be mathematically and computationally placed into a pending separate category.

Unless the AI developers have been extraordinarily cautious, the chances are that some notable level of these non-English words will be encapsulated during the data training across the selected portions of the Internet. One devised approach would be to simply discard any words that are calculated as possibly being non-English. This is not usually the case. Most generative AI is typically programmed to take a broad-brush approach.

The point is that a generative AI is unlikely to be of a single language purity.

Ive been discussing the case of using English as the primary language for being patterned. All other languages would be considered foreign with respect to English in that instance. Of course, we could readily and AI researchers have indeed chosen other languages to be the primary language for their generative AI efforts, which in that instance would mean that English is a foreign language in that case.

For purposes of this discussion, well continue with the case of English as selected as the primary language. The same precepts apply even if some other language is the selected primary language.

We can usually assume that the data training of a generative AI is going to include encounters with a multitude of other languages. If the encounters are sufficiently numerous, the mathematical and computational pattern matching will conventionally treat those as a separate category and pattern match them as based within this newly set aside category. Furthermore, pattern matching can mathematically and computationally broaden as the encounters aid in ferreting out the patterns of one language versus the patterns of a different language.

Here are some handy rules of thumb about what the generative AI is calculating:

As the pattern matching gets enhanced via the encounters with other languages, this also has the side benefit that when encountering yet another newly encountered language. The odds are that less of the language is needed to extrapolate what the language consists of. Smaller and smaller sample sizes can be extrapolated.

There is an additional corollary associated with that hypothesis.

Suppose that an additional language that well refer to for convenience as language Z had not been encountered at all during the data training. Later on, a user decides to enter a prompt into the generative AI that consists of that particular language Z.

You might at first assume that the generative AI would summarily reject the prompt as unreadable because the user is using a language Z that has not previously been encountered. Assuming that the AI developers were mindful about devising the generative AI to fully attempt to respond to any user prompt, the generative AI might shift into a language pattern-matching mode programmatically and try to pattern match on the words that otherwise seem to be outside of the norm or primary language being used.

This could account for the possibility that such a user-entered prompt elicits a surprising response by the generative AI in that the emitted response is also shown in the language Z, or that a response in say English is emitted and has seemingly discerned part of what the prompt was asking about. You see, the newly encountered language Z is parsed based on the pattern-matching generalizations earlier formed during data training as to the structure of languages.

During the 60 Minutes interview with Google executives, the exec that brought up the instance of generative AI that suddenly and surprisingly seemed to be able to respond to a prompt that was in Bengali, further stated that after some number of prompts in Bengali, the generative AI was able to seemingly translate all of Bengali. Heres what James Manyika, Googles SVP, stated: We discovered that with very few amounts of prompting in Bengali, it can now translate all of Bengali.

See the original post here:

Solving The Mystery Of How ChatGPT And Generative AI Can Surprisingly Pick Up Foreign Languages, Says AI Ethics And AI Law - Forbes

GCHQ chief Sir Jeremy Fleming has warned ministers about the risks posed by artificial intelligence (AI), amid growing debates about how to regulate the rapidly developing technology.

Downing Street gave little detail about what specific risks the GCHQ boss warned of but said the update was a clear-eyed look at the potential for things like disinformation and the importance of people being aware of that.

Prime minister Rishi Sunak used the same Cabinet meeting on Tuesday to stress the importance of AI to UK national security and the economy, No 10 said.

A readout of the meeting said ministers agreed on the transformative potential of AI and the vital importance of retaining public confidence in its use and the need for regulation that keeps people safe without preventing innovation.

The prime minister concluded Cabinet by saying that given the importance of AI to our economy and national security, this could be one of the most important policies we pursue in the next few years which is why we must get this right, the readout added.

Asked if the potential for an existential threat to humanity from AI had been considered, the PMs official spokesperson said: We are well aware of the potential risks posed by artificial general intelligence.

The spokesperson said Michelle Donelans science ministry was leading on that issue, but the governments policy was to have appropriate, flexible regulation which can move swiftly to deal with what is a changing technology.

As the public would expect, we are looking to both make the most of the opportunities but also to guard against the potential risk, the spokesperson added.

The government used the recent refresh of the integrated review to launch a new government-industry AI-focused task force on the issue, modelled on the vaccines task force used during the Covid pandemic.

Italy last month said it would temporarily block the artificial intelligence software ChatGPT amid global debate about the power of such new tools.

The AI systems powering such chatbots, known as large language models, are able to mimic human writing styles based on the huge trove of digital books and online writings they have ingested.

Mr Sunak, who created a new Department for Science, Innovation & Technology in a Whitehall reshuffle earlier this year, is known to be enthusiastic about making the UK a science superpower.

See the original post here:

GCHQ chiefs warning to ministers over risks of AI - The Independent

This feature is part of AI Week. For more stories, including How AI Could Doom Animation and comments from experts like Tim Sweeney, check out our hub.

All anyone wants to talk about in the games industry is AI. The technology once a twinkle in the eye of sci-fi writers and futurists has shot off like a bottle rocket. Every day we're greeted with fascinating and perturbing new advances in machine learning. Right now, you can converse with your computer on ChatGPT, sock-puppet a celebrity's voice with ElevenLabs, and generate a slate of concept art with MidJourney.

It is perhaps only a matter of time before AI starts making significant headway in the business of game development, so to kick off AI week at IGN, we talked to a range of experts in the field about their hopes and fears for this brave new world, and some are more skeptical than you'd expect.

AI Week Roundtable: Meet the Games Industry Experts

Pawel Sasko, CD Projekt Red Lead Quest Designer: I really believe that AI, and AI tools, are going to be just the same as when Photoshop was invented. You can see it throughout the history of animation. From drawing by hand to drawing on a computer, people had to adapt and use the tools, and I think AI is going to be exactly that. It's just going to be another tool that we'll use for productivity and game development.

Tim Sweeney, Epic Games CEO: I think there's a long sorting out process to figure out how all that works and it's going to be complicated. These AI technologies are incredibly effective when applied to some really bulk forms of data where you can download billions of samples from existing project and train on them, but that works for text and it works for graphics and maybe it will work for 3D objects as well, but it's not going to work for higher level constructs like games or the whole of the video game. There's just no training function that people know that can drive a game like that. I think we're going to see some really incredible advances and actual progress mixed in with the hype cycle where a lot of crazy stuff is promised. Nobody's going to be able to deliver.

Michael Spranger, COO of Sony AI: I think AI is going to revolutionize the largeness of gaming worlds; how real they feel, and how you interact with them. But I also think it's going to have a huge impact on production cycles. Especially in this era of live-services. We'll produce a lot more content than we did in the past.

Julian Togelius, Associate Professor of Computer Science at New York University, and co-author of the textbook Artificial Intelligence and Games: Long-term, we're going to see every part of game development co-created AI Designers will collaborate with AI on everything from prototyping, to concept art, to mechanics, balancing, and so on. Further on, we might see games that are actually designed to use AI during its runtime.

Pawel Sasko: There's actually many companies doing internal R&D of a specific implementation of not MidJourney especially, but literally just art tools like this, so that when you're in early concept phases, you're able to generate as many ideas as you can and just basically pick whatever works actually for you and then give it to an artist who actually developed that direction. I think it's a pretty intriguing direction because it opens up the doors that you wouldn't think of. And again, as an artist, we are just always limited by our skills that come up from all the life experiences and everything we have consumed artistically, culturally before. And AI doesn't have this limitation in a way. We can feed it so many different things, therefore it can actually propose so many different things that we wouldn't think of. So I think as a starting point or maybe just as a brainstorming tool, this could be interesting.

Michael Spranger: I think of AI as a creativity unlocking tool. There are so many more things you can do if you have the right tools. We see a rapid deployment of impact of this technology in content creation possibilities from 3D, to sound, to musical experiences, to what you're interacting with in a world. All of that is going to get much better.

Julian Togelius: Everybody looks at the image generation and text generation and say, 'Hey, we can just pop that into games.' And, of course, we see like proliferation of unserious, sometimes venture capital found that actors coming in and claiming that they're going to do all of your Game Arts with MidJourney these people usually don't know anything about game development. There's a lot of that going around. So I like to say that generating just an image is kind of the easy part. Every other part of game content, including the art, has so many functional aspects. Your character model must work with animations, your level must be completable. That's the had part.

Tim Sweeney: It's not synthesizing amazing new stuff, it's really just rewriting data that already exists. So, either you ask it to write a sorting algorithm in Python and it does that, but it's really just copying the structure of somebody else's code that it trained on. You tell it to solve a problem that nobody's solved before or the data it hasn't seen before and it doesn't have the slightest idea what to do about it. We have nothing like artificial general intelligence. The generated art characters have six or seven fingers, they just don't know that people have five fingers. They don't know what fingers are and they don't know how to count. They don't really know anything other than how to reassemble pixels in a statistically common way. And so, I think we're a very long way away from that, providing the kind of utility a real artist provides.

Sarah Bond, Xbox Head of Global Gaming Partnership and Development: We're in the early days of it. Obviously we're in the midst of huge breakthroughs. But you can see how it's going to greatly enhance discoverability that is actually customized to what you really care about. You can actually have things served up to you that are very, very AI driven. "Oh my gosh, I loved Tunic. What should I do next?

Tim Sweeney: I'm not sure yet. It's funny, we're pushing the state of the art in a bunch of different areas, but [Epic] is really not touching generative AI. We're amazed at what our own artists are doing in their hobby projects, but all these AI tools, data use is under the shadow, which makes the tools unusable by companies with lawyers essentially because we don't know what authorship claims might exist on the data.

Julian Togelius: I don't think it will affect anyone more than any other technology that forces people to learn new tools. You have to keep learning new tools or otherwise you'll become irrelevant. People will become more productive, and generate faster iterations. Someone will say, "Hey, this is a really interesting creature you've created, now give me 10,000 of those that differ slightly." People will master the tools. I don't think they will put anyone out of a job as long as you keep rolling with the punches.

Pawel Sasko: I think that the legal sphere is going to catch up with AI generation eventually, with what to do in these situations to regulate them. I know a lot of voice actors are worried about the technology, because the voice is also a distinct element of a given actor, not only the appearance and the way of acting. Legal is always behind us.

Michael Spranger: The relationship with creative people is really important to us. I don't think that relationship will change. When I go watch a Stanley Kubrick movie, I'm there to enjoy his creative vision. For us, it's important to make sure that those people can preserve and execute those creative visions, and that AI technology is a tool that can help make that happen.

Julian Togelius: Definitely. If you have a team that has deep expertise in every field, you're at an advantage. But I think we're gonna get to the point where, like, you only need to know a few fields to make a game, and have the AI tools be non-human standings for other fields of expertise. If you're a two-person team and you don't have an animator, you can ask the AI to do the animation for you. The studio can make a nice looking game even though they don't have all the resources. That's something I'm super optimistic about.

Tim Sweeney: I think the more common case, which we're seeing really widely used in the game industry is an artist does a lot of work to build an awesome asset, but then the procedural systems and the animation tools and the data scanning systems just blow it up to an incredible level.

Michael Spranger: Computer science in general has a very democratizing effect. That is the history of the field. I think these tools might inspire more people to express their creativity. This is really about empowering people. We're going to create much more content that's unlocked with AI, and I think it will have a role to play in both larger and smaller studios.

Michael Spranger: I think what makes this different is that the proof is in the pudding. Look at what Kazunori Yamuchi said about GT Sophy, [the AI-powered driver recently introduced to Gran Turismo 7]: there was a 25-year period where they built the AI in Gran Turismo in a specific way, and Yamuchi is basically saying that this is a new chapter. That makes a difference for me. When people are saying, "I haven't had this experience before with a game. This is qualitatively different." It's here now, you can experience it now.

Kajetan Kasprowicz, CD Projekt Red Cinematic Designer: Someone at GDC once gave a talk that basically said, "Who will want to play games that were made by AI?" People will want experiences created by human beings. The technology is advancing very fast and we kind of don't know what to do with it. But I think there will be a consensus on what we want to do as societies.

Julian Togelius: AI has actual use-cases, and it works, whereas all of the crypto shit was ridiculous grifting by shameless people. I hate that people associate AI with that trend. On the other hand you have something like VR, which is interesting technology that may, or may not, be ready for the mass market someday. Compare that to AI, which has hundreds of use-cases in games and game development.

Luke Winkie is a freelance writer at IGN.

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Tim Sweeney, CD Projekt, and Other Experts React to AI's Rise, and ... - IGN

The growth of Artificial Intelligence (AI) technologies and their deployment has raised questions about privacy, monopolisation and job losses. In a discussion moderated by Prashanth Perumal J., Ajay Shah and Apar Gupta discuss concerns about the economic and privacy implications of AI as countries try to design regulations to prevent the possible misuse of AI by individuals and governments. Edited excerpts:

Should we fear AI? Is AI any different from other disruptive technologies?

Ajay Shah: Technological change improves aggregate productivity, and the output of society goes up as a result. People today are vastly better off than they were because of technology, whether it is of 200 years ago or 5,000 years ago. There is nothing special or different this time around with AI. This is just another round of machines being used to increase productivity.

Apar Gupta: I broadly echo Ajays views. And alongside that, I would say that in our popular culture, quite often we have people who think about AI as a killer robot that is, in terms of AI becoming autonomous. However, I think the primary risks which are emerging from AI happen to be the same risks which we have seen with other digital technologies, such as how political systems integrate those technologies. We must not forget that some AI-based systems are already operational and have been used for some time. For instance, AI is used today in facial recognition in airports in India and also by law-enforcement agencies. There needs to be a greater level of critical thought, study and understanding of the social and economic impact of any new technology.

Ajay Shah: If I may broaden this discussion slightly, theres a useful phrase called AGI, which stands for artificial general intelligence, which people are using to emphasise the uniqueness and capability of the human mind. The human mind has general intelligence. You could show me a problem that I have never seen before, and I would be able to think about it from scratch and be able to try to solve it, which is not something these machines know how to do. So, I feel theres a lot of loose talk around AI. ChatGPT is just one big glorified database of everything that has been written on the Internet. And it should not be mistaken for the genuine human capability to think, to invent, to have a consciousness, and to wake up with the urge to do something. I think the word AI is a bit of a marketing hype.

Do you think the current regulatory system is equipped enough to deal with the privacy and competition threats arising from AI?

Ajay Shah: One important question in the field of technology policy in India is about checks and balances. What kind of data should the government have about us? What kind of surveillance powers should the government have over us? What are the new kinds of harm that come about when governments use technologies in a certain way? There is also one big concern about the use of modern computer technology and the legibility of our lives the way our lives are laid bare to the government.

Apar Gupta: Beyond the policy conversation, I think we also need laws for the deployment of AI-based systems to comply with Supreme Court requirements under the right to privacy judgment for specific use-cases such as facial recognition. A lot of police departments and a lot of State governments are using this technology and it comes with error rates that have very different manifestations. This may result in exclusion, harassment, etc., so there needs to be a level of restraint. We should start paying greater attention to the conversations happening in Europe around AI and the risk assessment approach (adopted by regulators in Europe and other foreign countries) as it may serve as an influential model for us.

Ajay Shah: Coming to competition, I am not that worried about the presence or absence of competition in this field. Because on a global scale, it appears that there are many players. Already we can see OpenAI and Microsoft collaborating on one line of attack; we can also see Facebook, which is now called Meta, building in this space; and of course, we have the giant and potentially the best in the game, Google. And there are at least five or 10 others. This is a nice reminder of the extent to which technical dynamism generates checks and balances of its own. For example, we have seen how ChatGPT has raised a new level of competitive dynamics around Google Search. One year ago, we would have said that the world has a problem because Google is the dominant vendor among search engines. And that was true for some time. Today, suddenly, it seems that this game is wide open all over again; it suddenly looks like the global market for search is more competitive than it used to be. And when it comes to the competition between Microsoft and Google on search, we in India are spectators. I dont see a whole lot of value that can be added in India, so I dont get excited about appropriating extraterritorial jurisdiction. When it comes to issues such as what the Indian police do with face recognition, nobody else is going to solve it for us. We should always remember India is a poor country where regulatory and state capacity is very limited. So, the work that is done here will generally be of low quality.

Apar Gupta: The tech landscape is dominated by Big Tech, and its because they have a computing power advantage, a data advantage, and a geopolitical advantage. It is possible that at this time when AI is going to unleash the next level of technology innovation, the pre-existing firms, which may be Microsoft, Google, Meta, etc., may deepen their domination.

How do you see India handling AI vis--vis Chinas authoritarian use of AI?

Ajay Shah: In China, they have built a Chinese firewall and cut off users in China from the Internet. This is not that unlike what has started happening in India where many websites are being increasingly cut off from Indian users. The people connected with the ruling party in China get monopoly powers to build products that look like global products. They steal ideas and then design and make local versions in China, and somebody makes money out of that. Thats broadly the Chinese approach and it makes many billion dollars of market cap. But it also comes at the price of mediocrity and stagnation, because when you are just copying things, you are not at the frontier and you will not develop genuine scientific and technical knowledge. So far in India, there is decent political support for globalisation, integration into the world economy and full participation by foreign companies in India. Economic nationalism, where somehow the government is supposed to cut off foreign companies from operating in India, is not yet a dominant impulse here. So, I think that there is fundamental superiority in the Indian way, but I recognise that there is a certain percentage of India that would like the China model.

Apar Gupta: I would just like to caution people who are taken in by the attractiveness of the China model it relies on a form of political control, which itself is completely incompatible in India.

How do you see Zoho Corporation CEO Sridhar Vembus comments that AI would completely replace all existing jobs and that demand for goods would drop as people lose their jobs?

Ajay Shah: As a card-carrying economist, I would just say that we should always focus on the word productivity. Its good for society when human beings produce more output per unit hour as that makes us more prosperous. People who lose jobs will see job opportunities multiplying in other areas. My favourite story is from a newspaper column written by Ila Patnaik. There used to be over one million STD-ISD booths in India, each of which employed one or two people. So there were 1-2 million jobs of operating an STD-ISD booth in India. And then mobile phones came and there was great hand-wringing that millions of people would lose their jobs. In the end, the productivity of the country went up. So I dont worry so much about the reallocation of jobs. The labour market does this every day prices move in the labour market, and then people start choosing what kind of jobs they want to do.

Ajay Shah is Research Professor of Business at O.P. Jindal Global University, Sonipat; Apar Gupta is executive director of the Internet Freedom Foundation

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Is the current regulatory system equipped to deal with AI? - The Hindu

The Victorian era was one transformed by the industrial revolution. The telegraph, telephone, electricity, and steam engine are key examples of life-changing technologies and machinery.

It is not surprising, therefore, that this real-life innovation sparked the imagination of writers like Robert Stevenson, Jules Verne, and H.G Wells.

These authors imagined time machines, space rockets, and telecommunication. Even Mark Twain wrote about mind-travelling, imagining a technology similar to the modern-day internet in 1898. Motifs such as utopias and dystopias became popular in literature as academics debated the scientific, cultural, and physiological impact of technology.

Robert Stevensons Strange Case of Dr Jekyll and Mr Hyde is another classic example. It explores the dangers of unchecked ambition in scientific experimentation through the evil, murderous alter ego Mr. Hyde. Mary Shellys Frankenstein unleashes a monster, a living being forged out of non-living materials. These stories spoke to the fear among the Victorian pious society that playing God would have deadly consequences.

In an FT op-ed, AI expert and angel investor Ian Hogarth refers to artificial general intelligence (AGI) as God-like AI for its predicted ability to generate new scientific knowledge independently and perform all human tasks. The article displayed both excitement and trepidation at the technologys potential.

According to GlobalData, there have been over 5,500 news items relating to AI in the past six months. Opinion ranges from unbridled optimism that AI will revolutionize the world, to theories of an apocalyptic future where machines will rise to render humanity obsolete.

In April 2023, The Future of Life Institute wrote an open letter calling for a six-month pause on developing AI systems that can compete with human-level intelligence, co-signed by tech leaders such as Elon Musk and Steve Wozniak. The letter posed the question Should we risk the loss of control of our civilization? as AI becomes more powerful. Over 3,000 people have signed it.

These arguments are the same as the talking points of Victorian sceptics on technological advancements. Philosopher and economist John Stuart Mill discussed in an essay entitled Civilization in which he wrote about the uncorrected influences of technological development on society, specifically the printing press, which he predicted would dilute the voice of intellectuals by making publishing accessible to the masses and commercialize the spread of knowledge. He called for national institutions to mitigate this impact.

Both were concerned with how technology could disrupt social norms and the labour market and wreak havoc on society as we know it. Both called for government oversight and regulation during a time of intense scientific progress.

In the 1800s, the desire to push boundaries won out over concerns, breeding a new class of innovators and entrepreneurs. Without this innovative spirit, Alexander Graham Bell would not have invented the telephone in 1876, and Joseph Swan would not have invented the lightbulb in 1878. They were the forerunners to the Bill Gates and Jeff Bezos of this world.

While technology advances at a rapid pace, human behaviour remains consistent. In other words, advances in technology will always divide opinions between those who view it as a new frontier to explore and those who consider it to be Frankensteins monster. We can heed the warnings when it comes to unregulated technological developments and still appreciate the opportunities ingenuity brings. This is especially pertinent when it comes to artificial intelligence.

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How would a Victorian author write about generative AI? - Verdict