Archive for the ‘Artificial Intelligence’ Category

Has Google’s LaMDA artificial intelligence really achieved sentience? – New Scientist

Blake Lemoine, an engineer at Google, has claimed that the firm's LaMDA artificial intelligence is sentient, but the expert consensus is that this is not the case

By Matthew Sparkes

Google is developing a range of artificial intelligence models

KENZO TRIBOUILLARD/AFP via Getty Images

A Google engineer has reportedly been placed on suspension from the company after claim that an artificial intelligence (AI) he helped to develop had become sentient. If I didnt know exactly what it was, which is this computer program we built recently, Id think it was a seven-year-old, eight-year-old kid, Blake Lemoine told the Washington Post.

Lemoine released transcripts of conversations with with the AI, called LaMDA (Language Model for Dialogue Applications), in which it appears to express fears of being switched off, talk about how it feels happy and sad, and attempts to form bonds with humans by talking about situations that it could never have actually experienced. Heres everything you need to know.

In a word, no, says Adrian Weller at the Alan Turing Institute.

LaMDA is an impressive model, its one of the most recent in a line of large language models that are trained with a lot of computing power and huge amounts of text data, but theyre not really sentient, he says. They do a sophisticated form of pattern matching to find text that best matches the query theyve been given thats based on all the data theyve been fed.

Adrian Hilton at the University of Surrey, UK agrees that sentience is a bold claim thats not backed up by the facts. Even noted cognitive scientist Steven Pinker weighed in to shoot down Lemoines claims, while Gary Marcus at New York University summed it up in one word: nonsense.

Neither Lemoine nor Google responded to New Scientists request for comment. But its certainly true that the output of AI models in recent years has become surprisingly, even shockingly good.

Our minds are susceptible to perceiving such ability especially when it comes to models designed to mimic human language as evidence of true intelligence. Not only can LaMDA make convincing chit-chat, but it can also present itself as having self-awareness and feelings.

As humans, were very good at anthropomorphising things, says Hilton. Putting our human values on things and and treating them as if they were sentient. We do this with cartoons, for instance, or with robots or with animals. We project our own emotions and sentience onto them. I would imagine thats whats happening happening in this case.

It remains unclear whether the current trajectory of AI research, where ever-larger models are fed ever-larger piles of training data, will see the genesis of an artificial mind.

I dont believe at the moment that we really understand the mechanisms behind what what makes something sentient and intelligent, says Hilton. Theres a lot of hype about AI, but Im not convinced that what were doing with machine learning, at the moment, is really intelligence in that sense.

Weller says that, given human emotions rely on sensory inputs, it might eventually be possible to replicate them artificially. It potentially, maybe one day, might be true, but most people would agree that theres a long way to go.

The Washington Post claims that Lemoine has been placed on suspension after seven years at Google, having attempted to hire a lawyer to represent LaMDA and sending executives a document that claimed the AI was sentient. Google also says that publishing the transcripts broke confidentiality policies.

Google told the Washington Post that: Our team, including ethicists and technologists, has reviewed Blakes concerns per our AI principles and have informed him that the evidence does not support his claims. He was told that there was no evidence that LaMDA was sentient (and lots of evidence against it).

Lemoine responded on Twitter: Google might call this sharing proprietary property. I call it sharing a discussion that I had with one of my coworkers.

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Has Google's LaMDA artificial intelligence really achieved sentience? - New Scientist

The Worldwide Artificial Intelligence (AI) Robots Industry is Expected to Reach $38.3 Billion by 2027 – GlobeNewswire

Dublin, June 13, 2022 (GLOBE NEWSWIRE) -- The "Global Artificial Intelligence (AI) Robots Market (2022-2027) by Offering, Robot, Technology, Deployment Mode, Application, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence (AI) Robots Market is estimated to be USD 7.1 Bn in 2022 and is projected to reach USD 38.32 Bn by 2027, growing at a CAGR of 40.1%.

Market Dynamics

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence (AI) Robots Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Company Profiles

The report provides a detailed analysis of the competitors in the market. It covers the financial performance analysis for the publicly listed companies in the market. The report also offers detailed information on the companies' recent development and competitive scenario. Some of the companies covered in this report are ABB Industries, F&P Personal Robotics, Hanson Robotics, Harman International, IBM, Intel, LG Electronics, Microsoft, Rethink Robotics, SoftbankXilinx,, etc.

Countries Studied

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence (AI) Robots Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The report analyses the Global Artificial Intelligence (AI) Robots Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.

Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Key Topics Covered:

1 Report Description

2 Research Methodology

3 Executive Summary

4 Market Dynamics4.1 Drivers4.1.1 High Adoption of Robots for Personal Use, Automation and mainly in Healthcare Industry4.1.2 Support to Such Robots from Governments Worldwide4.2 Restraints4.2.1 Absence of Standardized Regulations to Prevent Risks Associated With Networked and Autonomous Robots4.2.2 Reluctance to Adopt New Technologies4.3 Opportunities4.3.1 Focus on Developing Robots with Special Application Cases 4.3.2 Increasing Aging Population Worldwide Boosting the Demand for AI-based Robots for Elderly Assistance4.4 Challenges4.4.1 Developing Ai to Help Robots Make Better Decisions and Make Them Safe for Humans4.4.2 Long Time to Commercialize Robots and High Maintenance Cost

5 Market Analysis5.1 Regulatory Scenario5.2 Porter's Five Forces Analysis5.3 Impact of COVID-195.4 Ansoff Matrix Analysis

6 Global Artificial Intelligence (AI) Robots Market, By Offering6.1 Introduction6.2 Hardware 6.3 Software

7 Global Artificial Intelligence (AI) Robots Market, By Robot7.1 Introduction7.2 Service Robots7.2.1 Ground7.2.2 Aerial7.2.3 Underwater7.3 Industrial Robots7.3.1 Traditional Industrial Robots7.3.2 Collaborative Industrial Robots

8 Global Artificial Intelligence (AI) Robots Market, By Technology8.1 Introduction8.2 Computer Vision8.3 Context Awareness8.4 Machine Learning8.5 Natural Language Processing

9 Global Artificial Intelligence (AI) Robots Market, By Deployment Mode9.1 Introduction9.2 Cloud 9.3 On-Premise

10 Global Artificial Intelligence (AI) Robots Market, By Application10.1 Introduction10.2 Agriculture10.3 Education & Entertainment10.4 Healthcare Assistance10.5 Industrial10.6 Law Enforcement10.7 Military & Defence10.8 Personal Assistance & Care giving10.9 Public Relations10.10 Research & Space exploration10.11 Security & Surveillance10.12 Stock Management

11 Americas' Artificial Intelligence (AI) Robots Market11.1 Introduction11.2 Argentina11.3 Brazil11.4 Canada11.5 Chile11.6 Colombia11.7 Mexico11.8 Peru11.9 United States11.10 Rest of Americas

12 Europe's Artificial Intelligence (AI) Robots Market12.1 Introduction12.2 Austria12.3 Belgium12.4 Denmark12.5 Finland12.6 France12.7 Germany12.8 Italy12.9 Netherlands12.10 Norway12.11 Poland12.12 Russia12.13 Spain12.14 Sweden12.15 Switzerland12.16 United Kingdom12.17 Rest of Europe

13 Middle East and Africa's Artificial Intelligence (AI) Robots Market13.1 Introduction13.2 Egypt13.3 Israel13.4 Qatar13.5 Saudi Arabia13.6 South Africa13.7 United Arab Emirates13.8 Rest of MEA

14 APAC's Artificial Intelligence (AI) Robots Market14.1 Introduction14.2 Australia14.3 Bangladesh14.4 China14.5 India14.6 Indonesia14.7 Japan14.8 Malaysia14.9 Philippines14.10 Singapore14.11 South Korea14.12 Sri Lanka14.13 Thailand14.14 Taiwan14.15 Rest of Asia-Pacific

15 Competitive Landscape15.1 Competitive Quadrant15.2 Market Share Analysis15.3 Strategic Initiatives15.3.1 M&A and Investments15.3.2 Partnerships and Collaborations15.3.3 Product Developments and Improvements

16 Company Profiles 16.1 ABB Industries16.2 Alphabet16.3 Blue Frog Robotics16.4 Boston Dynamics16.5 Comau16.6 Diligent Robotics16.7 F&P Personal Robotics16.8 FANUC16.9 FRANKA EMIKA 16.10 Hanson Robotics 16.11 Harman International16.12 IBM 16.13 Intel 16.14 jibo16.15 KUKA16.16 LG Electronics 16.17 Microsoft 16.18 Neurala16.19 Pal Robotics 16.20 Promobot16.21 Rethink Robotics16.22 Softbank16.23 Staubli16.24 Xilinx

17 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/p6baqx

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The Worldwide Artificial Intelligence (AI) Robots Industry is Expected to Reach $38.3 Billion by 2027 - GlobeNewswire

Global Artificial Intelligence in Supply Chain Market (2022 to 2027) – Growing Cloud-Based Applications Adoption Presents Opportunities -…

DUBLIN--(BUSINESS WIRE)--The "Global Artificial Intelligence in Supply Chain Market (2022-2027) by Offering, Technology, Application, Industry, Geography, Competitive Analysis, and the Impact of Covid-19 with Ansoff Analysis" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence in Supply Chain Market is estimated to be USD 3.3 Bn in 2022 and is projected to reach USD 10.49 Bn by 2027, growing at a CAGR of 26.02%.

Market dynamics are forces that impact the prices and behaviors of the Global Artificial Intelligence in Supply Chain Market stakeholders. These forces create pricing signals which result from the changes in the supply and demand curves for a given product or service. Forces of Market Dynamics may be related to macro-economic and micro-economic factors. There are dynamic market forces other than price, demand, and supply. Human emotions can also drive decisions, influence the market, and create price signals.

As the market dynamics impact the supply and demand curves, decision-makers aim to determine the best way to use various financial tools to stem various strategies for speeding the growth and reducing the risks.

Competitive Quadrant

The report includes Competitive Quadrant, a proprietary tool to analyze and evaluate the position of companies based on their Industry Position score and Market Performance score. The tool uses various factors for categorizing the players into four categories. Some of these factors considered for analysis are financial performance over the last 3 years, growth strategies, innovation score, new product launches, investments, growth in market share, etc.

Ansoff Analysis

The report presents a detailed Ansoff matrix analysis for the Global Artificial Intelligence in Supply Chain Market. Ansoff Matrix, also known as Product/Market Expansion Grid, is a strategic tool used to design strategies for the growth of the company. The matrix can be used to evaluate approaches in four strategies viz. Market Development, Market Penetration, Product Development and Diversification. The matrix is also used for risk analysis to understand the risk involved with each approach.

The report analyses the Global Artificial Intelligence in Supply Chain Market using the Ansoff Matrix to provide the best approaches a company can take to improve its market position.

Based on the SWOT analysis conducted on the industry and industry players, the analyst has devised suitable strategies for market growth.

Why buy this report?

Market Dynamics

Drivers

Restraints

Opportunities

Challenges

Market Segmentations

The Global Artificial Intelligence in Supply Chain Market is segmented based on Offering, Technology, Application, Industry, and Geography.

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/hx4h3q

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Global Artificial Intelligence in Supply Chain Market (2022 to 2027) - Growing Cloud-Based Applications Adoption Presents Opportunities -...

Is Artificial Intelligence the future of art? : – The Tico Times

To many they are arts next big thing digital images of jellyfish pulsing and blurring in a dark pink sea, or dozens of butterflies fusing together into a single organism.

The Argentine artist Sofia Crespo, who created the works with the help of artificial intelligence, is part of the generative art movement, where humans create rules for computers which then use algorithms to generate new forms, ideas and patterns.

The field has begun to attract huge interest among art collectors and even bigger price tags at auction.

US artist and programmer Robbie Barrat a prodigy still only 22 years old sold a work called Nude Portrait#7Frame#64 at Sothebys in March for 630,000 ($821,000).

That came almost four years after French collective Obvious sold a work at Christies titled Edmond de Belamy largely based on Barrats code for $432,500.

Collector Jason Bailey told AFP that generative art was like a ballet between humans and machines.But the nascent scene could already be on the verge of a major shake-up, as tech companies begin to release AI tools that can whip up photo-realistic images in seconds.

Artists in Germany and the United States blazed a trail in computer-generated art during the 1960s.

The V&A museum in London keeps a collection going back more than half a century, one of the key works being a 1968 piece by German artist Georg Nees called Plastik 1.

Nees used a random number generator to create a geometric design for his sculpture.

Nowadays, digital artists work with supercomputers and systems known as Generative Adversarial Networks (GANs) to create images far more complex than anything Nees could have dreamed of.

GANs are sets of competing AIs - one generates an image from the instructions it is given, the other acts as a gatekeeper, judging whether the output is accurate.

If it finds fault, it sends the image back for tweaks and the first AI gets back to work for a second try to beat the gamekeeper.But artists like Crespo and Barrat insist that the artist is still central to the process, even if their working methods are not traditional.

When Im working this way, Im not creating an image. Im creating a system that can create images, Barrat told AFP.

Crespo said she thought her AI machine would be a true collaborator, but in reality it is incredibly tough to get even a single line of code to generate satisfactory results.

She said it was more like babysitting the machine. Tech companies are now hoping to bring a slice of this rarefied action to regular consumers.

Google and Open AI are both touting the merits of new tools they say bring photorealism and creativity without the need for coding skills.

They have replaced GANs with more user-friendly AI models called transformers that are adept at converting everyday speech into images.

Google Imagens webpage is filled with absurdist images generated by instructions such as: A small cactus wearing a straw hat and neon sunglasses in the Sahara desert.

Open AI boasts that its Dalle-2 tool can offer any scenario in any artistic style from the Flemish masters to Andy Warhol.

Although the arrival of AI has led to fears of humans being replaced by machines in fields from customer care to journalism, artists see the developments more as an opportunity than a threat.

Crespo has tried out Dalle-2 and said it was a new level in terms of image generation in general though she prefers her GANs. I very often dont need a model that is very accurate to generate my work, as I like very much when things look indeterminate and not easily recognizable, she said.

Camille Lenglois of Pariss Pompidou Centre Europes largest collection of contemporary art also played down any idea that artists were about to be replaced by machines.

She told AFP that machines did not yet have the critical and innovative capacity, adding: The ability to generate realistic images does not make one an artist.

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Is Artificial Intelligence the future of art? : - The Tico Times

Where Does Legal Accountability Rest Between Tesla’s Artificial Intelligence and Human Error? – Above the Law

Self-driving cars are nifty. Electric vehicles are cool. And when you think of self-driving electric cars, its hard not to think of Tesla. That said, not everyone associates them with safety. And with how the AIs algorithmic thinking is looking, they may have good reason.

On Thursday, the National Highway Traffic Safety Administration, an agency under the guidance of Transportation Secretary Pete Buttigieg, said it would be expanding a probe and look into830,000 Tesla carsacross all four current model lines, 11% more vehicles than they were previously examining.

Initially the probe started last year in response to Tesla vehicles mysteriously plowing into the scene of an existing accident where first responders were already present.

On Thursday, NHTSA said it had discovered in 16 separate instances when this occurred that Autopilot aborted vehicle control less than one second prior to the first impact, suggesting the driver was not prepared to assume full control over the vehicle.

CEO Elon Musk hasoften claimedthat accidents cannot be the fault of the company, as data it extracted invariably showed Autopilot was not active in the moment of the collision.

At least 26 crashes and 11 deaths appear to involve Teslas autopilot feature. While it is true that drivers should have their hands at 10 and 2 with their eyes on the road, youve gotta admit that there have been some representations of the autopilot feature as a replacement for human inputs. A last-minute shift from AI to UI is exactly the type of childish loopholing masquerading as brilliance youd expect from a guy with an Elden Ring build this bad.

Look, I know Ive made that gag in a prior article where I dunked on Musk for being goofy, BUT TWO MEDIUM SHIELDS?

For fear of being labeled a one-trick Tesla with weak windows this is exactly what youd expect from a guy who was already on trial for killing someone with a car.

Whats next? A special re-issue of O.J. Simpsons If I Did It with an additional chapter from Elon on how hed use tweets to manipulate stock prices?

Cartoonish evil gets satirical responses. In the meantime, it may be worth it to consider electric car alternatives that arent Teslas. And pay attention to the road, damn it.

Elon Musks Regulatory Woes Mount As U.S. Moves Closer To Recalling Teslas Self-Driving Software [Fortune]

Chris Williams became a social media manager and assistant editor for Above the Law in June 2021. Prior to joining the staff, he moonlighted as a minor Memelord in the Facebook groupLaw School Memes for Edgy T14s. He endured Missouri long enough to graduate from Washington University in St. Louis School of Law. He is a former boatbuilder who cannot swim,a published author on critical race theory, philosophy, and humor, and has a love for cycling that occasionally annoys his peers. You can reach him by email atcwilliams@abovethelaw.comand by tweet at@WritesForRent.

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Where Does Legal Accountability Rest Between Tesla's Artificial Intelligence and Human Error? - Above the Law