STR in Isaac Sim with dolly.

Building cars at BMW involves the handling of millions of parts flowing into a factory from more than 4,500 supplier sites. One factor increasing the factory logistics challenge for the BMW Group is the customizability offered by the company. With an average of 100 different options available, this translates into 99% of customer orders being unique to each customer.

Ultimately, the sheer volume of possible configurations became a challenge to BMW Group production in three fundamental areascomputing, logistics planning, and data analysis, said Jurgen Maidl, senior vice president of logistics for the BMW Group.

Nvidia Isaac robotics platform working in sync with robot.To better handle logistics within its factories, BMW now uses four types of material handling robots and a smart transport robot. These robots were developed using Nvidias Isaac robotics platform.

According to Nvidia, its Isaac software development kit provides these robots with neural networks capable of addressing perception, segmentation, and human pose estimation to perceive their environment, detect objects, navigate autonomously and move objects. These robots are trained both on real and synthetic data using Nvidia graphics processing units (GPUs) to render ray-traced machine parts in a variety of lighting and occlusion conditions to augment real data.

Hanns Huber of BMWHanns Huber, with BMW Groups Communications Production Network, explained how the five different types of robots the company outfitted with Nvidias technology support factory logistics in production operations.

He said that, after delivery to the plant, parts are transported to the assembly line in containers of various sizes. Stationary SplitBots take full plastic boxes from the pallet in the incoming goods area and place them on a conveyor system that transports the boxes to a warehouse. The SplitBot also makes sure the containers are lined up correctly for automated storage. Using Nvidias artificial intelligence, the SplitBot can detect and process up to 450 different containers.

Mobile PlaceBots unload tugger trains and place boxes loaded with goods on a shelf. These robots use Nvidias image recognition system to classify the small load carriers and determine the ideal grip point from the combined input of sensors, cameras, and artificial intelligence. These technologies allow the PlaceBots to move autonomously in a predetermined area.

Another logistics robot, the PickBot has a robotic arm that it uses to collect various small parts from supply racks. Like the SplitBots, the PickBot uses Nvidias AI technology to calculate the right grip point.

The robotic manipulation arm of the SortBot takes empty boxes and puts them on a palette to be sent back to supplier area. These SortBots are deployed in series production to stack empty containers on pallets before they re-enter circulation.

BMWs autonomous Smart Transport Robots (STRs) can identify obstacles such as forklift trucks, as well as humans, to more accurately and quickly suggest alternative routes as needed. They can also learn from the environment and apply different responses to people and objects.

Huber noted that all of these robots have been developed by BMW in the past five years, with most being deployed and tested in BMW factories since 2019. The robots are trialed during our development process at various BMW plants in Germany, as well at our logistics laboratory in Munich, he explained.

The STR was developed by BMWs logistics innovation team together with Fraunhofer Institute Dortmund, Huber added.

STR Robot in BMW facility.BMWs work with Nvidia on this project began in 2019. A BMW Group team of engineers worked on implementing the Nvidia technology with the robots, Huber said. The complete implementation was done in-house at BMW. Two teams from both sidesBMW Group and Nvidiaworked closely to customize and adapt a suitable solution. The first STR with Nvidia technology was deployed as a proof-of-technology in our logistics laboratory in Munich in May 2020. The first productive test will go live by the forth quarter of 2020.

Nvidia notes that the real and synthetic data generated during the testing of these robots are used to train deep neural networks on Nvidias DGX AI infrastructure development systems. The robots are then continuously tested in Nvidias Isaac Sim simulators for navigation and manipulation development, operating on Nvidias Omniverse platform, where multiple BMW Group personnel in different geographies can all work in one simulated environment.

Huber said that, incorporating Nvidias AI technology into BMWs robots allows BMW to optimize our robotics and material flow, as well as take simulations in the planning process to a new level.

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BMW Outfits Robots with Artificial Intelligence - Automation World

AI expert Beth Singler was on hand to fill us in...

Beth - Yeah. So lots of people have tried to come up with ways to show or describe, or explain intelligence and specifically artificial intelligence. And we've mostly gone down the line of thinking; there are ways to test for intelligence, and that really tells us more about what we think intelligence is. And actually, whether we'll be able to prove intelligence in an artificial entity or machine. I'm really quite fond of a quote from someone called Robert Wilensky, who was a computer scientist working in AI at the very beginning. And he says that very early scientists working on AI were mathematicians, and they looked around and they said, well, we're smart. So if an artificial intelligence is going to be smart, it's going to be able to do the things we can do. And as mathematicians, they could basically prove theorems and play chess. So these same sorts of ideas are now constantly mapped onto what we think AI is going to be able to do to be smart. Whereas I think there might be something interesting in thinking about how an AI might work against our assumptions and programming and be able to do things that are unexpected and unexplained, but also those could theoretically be programmed into it. So it's all very complicated, but I think it does tell us something very, very profound about why we think intelligence is measurable by being able to play chess really well, or Go very well or prove a theorem.

Phil - So are there some under appreciated aspects of quote unquote intelligence, that you think people making these AIs needs to pay more attention to or are starting to pay more attention to?

Beth - Well, we are very aware that intelligence is embodied. Scientists look at cognition through embodiment and as an anthropologist, as a social scientist, I see how an intelligence is a relational thing that we have in community through our human bodies. So increasingly the speculations about how we develop actual humanlike intelligence in machines, would have to require some sort of learning process within an embodied sensory system, and there's work going in that direction. But to simply say, you're intelligent, if you can play chess very well, that that would make me a very not intelligent person. And I hope I am a relatively intelligent person, but I cannot play chess. So there are levels and standards that we have set for intelligence, for our machines and artificial intelligence, but we need to think about how it works in the whole.

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How could we know if an artificial intelligence is really intelligent? - The Naked Scientists

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Google, IFlyTek, Baidu, Microsoft, SAP, IBM, Brighterion, Intel, KITT.AI, Salesforce, Ipsoft, Ada Support, NanoRep(LogMeIn), Megvii Technology, Brainasoft, H2O.ai, IDEAL.com, Yseop, Albert Technologies, Astute Solutions and Wipro

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Artificial Intelligence Software Market by Technology Innovations and Growth 2020 to 2025 - CueReport

Alliance to Benefit Industry 4.0 and SMART Factory Initiatives

ATLANTA, June 23, 2020 /PRNewswire/ --ProcessMinerTM, an artificialintelligence platform for manufacturing, and Litmus, the Intelligent Edge Computing Platform for IIoT, today announced a partnership to cross-promote their industry-leading platforms to offer manufacturers a solution that includes real-time data collection, analysis, prediction and process recommendations for continuous improvement.

Litmus provides the data intelligence platform to quickly collect, normalize and analyze high volumes of live data from industrial assets and make it available to OT and IT systems via edge-to-enterprise integration.The ProcessMiner program uses machine learning and sensor data to model, predict and prescribe process control recommendations for product quality improvement purposes.

"Litmus offers something to our customers that is mission-critical," said Karim Pourak, CEO and Co-founder, ProcessMiner. "As customers invest in technology to improve product quality, reduce scrap rates and improve yield, secure access to the incoming data has to be accurate and normalized to ensure the integrity of our predictions and recommendations downstream. Litmus solves that problem for us."

"Process improvement is one of the primary goals for our customers and partnering with ProcessMiner allows us to give them an even stronger offering with cutting-edge AI technology," said JohnYounes, co-founder and COO, Litmus. "We provide the intelligence at the edge, and the power of ProcessMiner's AI will go a long way toward driving measurable ROI for customers looking to further predict quality and make actionable recommendations for manufacturing processes."

One of the unique benefits of the Litmus platform is the bidirectional data and signal delivery capabilities for machines on the factory floor. The Litmus platform quickly collects and normalizes data in real-time at the edge.

After Litmus delivers data to the ProcessMiner platform, the corrective action or recommendation signals can securely and automatically be sent back to the appropriate machine controller usingLitmus Edge. Those signals drive process control activities on the machine automatically, delivering corrective action(s) in real-time.

Under terms of the agreement, both organizations will promote their respective platform capabilities throughout the manufacturing industry.

ABOUT PROCESSMINER:Founded in 2014, the ProcessMiner platform predicts problems in real-time using AI within the manufacturing process. The platform is being rapidly adopted by the Tissue and Packaging industries, inclusive of manufacturers in the Pulp, Paper and Plastics industries and pilot projects are underway with water treatment and energy sectors of manufacturing. For more information, visitwww.processminer.com.

ABOUT LITMUS:Litmus enables out-of-the-box data collection, analytics, and management with an Intelligent Edge Computing Platform for IIoT. Litmus provides the solution to transform critical edge data into actionable intelligence that can power predictive maintenance, machine learning, and AI. Customers include 10+ Fortune 500 manufacturing companies, while partners like Siemens, HPE, Intel and SNC Lavalin expand the Company's path to market. For more information, visitwww.litmus.io.

Media Contact:

Allison YrungarayPublic Relations Manager, Litmusallison.yrungaray@litmus.io

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Litmus Partners With ProcessMiner to Offer Leading Edge Computing and Artificial Intelligence Platforms for Manufacturing - Yahoo Finance

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Global Artificial Intelligence in Accounting Market is accounted for xx USD million in 2019 and is expected to reach xx USD million by 2025 growing at...

Artificial Intelligence virtual waiter pioneered to get restaurants and bars back up and running.

An AI powered digital waiter, w8r.ai, has launched to help restaurants, cafes and bars to safely re-open their doors ahead of todays announced 4th July lockdown lifting.

W8R.ai can chat to the customer, guide through the digital menu, suggest dishes and specials and even recommend wine pairing. Diners can see their dishes in augmented reality in front of them or watch their food being prepared with live streaming from the kitchen. Bar customers can use video technology to safely chat with bar staff about a cocktail creation or order another round with a tap of the phone.

The AI waiter doesnt require an app or downloads and doesnt require customers to hand over any data. Customers simply use their phone camera to scan a QR code on their table. This launches the w8r.ai service for the establishment. Any orders are instantly routed with table number details direct to the venues bar or kitchen. It uses advanced natural language processing technology as well as a machine learning algorithm to get better and better with every use.

There are a multitude of order at table services, but the experience provided can be very sterile and bland. Its like ordering a take-away but sitting in the restaurant. W8R.ai goes much deeper and enables venues to provide a dining or drinking experience says founder Craig Holt.

W8R.ai incorporates video conferencing technology to further enhance the experience. Video opens up a world of possibilities added Holt. A world class sommelier could work at multiple restaurants at once using video conferencing.

There is also the ability to exchange messages with the venues actual staff or to call someone over to the table. Each W8R experience is built bespoke to the venue: the balance between human and digital interaction, the words used, the presentation of the menu or the interaction - everything is built around the brand and personality of the venue to create an unforgettable experience for the customer.

Please contact Daisy Craydon PR for interview requests, further images or quotes from Founder Craig Holt on 07539494720 or email contact@daisycraydonpr.com

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BREAKING NEWS: Artificial Intelligence virtual waiter pioneered to get restaurants and bars back up and running - ResponseSource

The Verge is a place where you can consider the future. So are movies. In Yesterdays Future, we revisit a movie about the future and consider the things it tells us about today, tomorrow, and yesterday.

The movie: A.I. Artificial Intelligence

The future: A.I. begins with a brief summary of the sorry state of the world: climate change has melted the polar ice caps, wiping out coastal cities and severely reducing the human population. With regulations in place for reproduction on a resource-starved planet, corporations developed Mecha androids that appear human but lack emotions. Theyre seen as objects useful for labor or sex work, just human enough to not be strange but machine enough to not mistake them for people.

The story kicks into gear when Professor Allen Hobby (William Hurt) pitches taking Mecha to the next level: a machine that can love. That Mecha becomes David (Haley Joel Osment), an experimental Mecha designed to imprint on his owners and love them unconditionally, forever. And it works David is given to a grieving couple whose son is in suspended animation due to a rare disease. After some hijinks, hes accepted, until Martin, the boy hes filling in for, comes back.

Unfortunately Martin is cruel, and thanks to his manipulation, David is forced from home into a Pinocchio-esque journey to find a Blue Fairy and become a real boy. Through his eyes, we see a nihilistic theme-park vision of the future, where little is done to solve the still-looming climate apocalypse but neon cities and their pleasures boom.

The past: A.I. was released in 2001, but was originally going to come out long before that. Based on Brian Aldiss 1969 short story Supertoys Last All Summer Long, the film began as a Stanley Kubrick project in the 70s, languishing in development hell until the famed directors death in 1999. Steven Spielberg then took over, reportedly hewing closely to the plans Kubrick had for the film.

This meant that, at the time, the critical reception of A.I. largely revolved around its status as a strange hybrid of Kubrick and Spielbergs sensibilities, the last work of an idiosyncratic master carried out by one of his most prominent and stylistically different admirers. Most, like Roger Ebert, felt that the result was a frustrating film, attempting to parse where one mans vision ended and the others began.

But A.I. was an extremely fitting film for 2001, a year characterized by cinematic restlessness. Unsettling arthouse classics Donnie Darko and Mulholland Drive premiered. Shrek, which skewered Disney-style fairy tales with pop culture cynicism, also arrived, unwittingly laying the groundwork for surreal internet memes a decade later. Films that would spawn, extend, or hope to begin franchises floundered in every direction, with understated hits like Oceans Eleven arriving alongside strange blockbusters like Jurassic Park III and showstoppers like The Fellowship of the Ring.

No one knew what the 21st century would mean for movies, and a sad sci-fi fairytale about a robot boy created to stand in the void between a bleak future and an idyllic past could not have been a better match for the times.

The present: At first glance, the hedonistic carnival of A.I.s cities do not seem to hew terribly close to our current moment. Like a lot of cinematic futures, this one seems too loud, too garish, to ever be real. Jude Law as Gigolo Joe? The horrific robot bloodsport of the Flesh Fair, where obsolete robots battle to the death? We dont really have anything like that yet, right?

Only we do. The seeds of this future have already bloomed in our present. Its subtext is our subtext, a world formed by people with all the power afforded them by technology but none of the will to dream or love. The former would demand a clear-eyed response to shared crises looming ahead both at home and abroad; the latter would lead us to wield our innovations compassionately. Instead we have a world where algorithms reinforce biases and outrage is commodified, where every innovation is part and parcel with a new indignity. A lack of humanity that at every turn denies the option of a better future for all in favor of a more extravagant present for a few.

In A.I.s final 20 minutes, its revealed that this is the end of the world. In 2,000 more years, climate change will claim the last habitable portion of the Earth, and David will be the only one left who remembers humanity. Still a child, all David wants to remember is the human mother he imprinted on, but the viewer remembers everything else that the world was doomed by rage at the pending self-imposed disaster that humanity refused to face and instead directed toward the Mecha they created, the Mecha that would outlast them.

They made us too smart, too quick, and too many, Gigolo Joe, the Mecha sexbot that becomes Davids unlikely companion, says in one of his final scenes. In the end, all that will be left is us. Thats why they hate us

A.I. is refreshing because it is not interested in the question of whether or not we should create self-aware synthetic life, but instead asks what our responsibility toward it would be. If you can create a robot to love a human, one character asks early in the film, how do you get a human to love them back?

In the end it doesnt matter. Humanity doesnt even love itself enough to ensure its own survival.

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A.I. Artificial Intelligence shows us a future where we neglect to dream - The Verge