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IBM Has Patented a Coffee Delivery Drone that Knows When You’re Tired

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Do we really need a drone to read our heart rates and eye movements to know we need a cup of java?

f you’ve grown weary of neck-bearded baristas in flannel and waiting in line for £5 eight-ounce cold brews, then you’ll be happy to know that soon you may be able to avoid that experience altogether in order to get your morning caffeine fix. The harbinger of death for the third-wave coffee shop has arrived, and it has taken the form of a coffee-delivering drone, designed by none other than IBM. And it knows when you need a jolt probably before you even do.

According to a patent document made available to the public by the US Patent and Trademark Office, IBM was granted a patent for an unmanned aerial vehicle, or UAV, that delivers coffee or another “caffeine containing drink” to an individual who has placed an order, or to an individual in a crowd “for whom an electronic analysis of sensor data indicates to be in a predetermined cognitive state” requiring caffeine. All this means that a coffee-carrying drone could use various forms of electronic analysis to predict who needs a pick-me-up and who doesn’t, including motion sensors to know if someone’s head might be drooping in a mid-afternoon lull, or reading Fitbit data to know what time someone might have just woken up and be in need of a jolt. If given access to your medical data, it would know if you’re taking medication that interacts badly with caffeine, and would skip you over.

The patent for this drone, designed with office buildings or public event spaces like convention halls or festivals in mind, was first filed back in 2015 by IBM, the company known for creating business technologies that changed the way the world does work. The company currently holds record for the most US patents generated by a business for 25 consecutive years, according to Wikipedia.

 

It’s not the first company to develop a coffee delivery system that uses drones. Last year, a drone-focused logistics company called Matternet tested its coffee delivery via drone in the skies of Zurich, Switzerland. Back in 2014, an Amsterdam-based company called Coffee Copter demonstrated a version of its own system, which relied on an app as the user interface for placing coffee orders in an office setting. Just this past Monday, Wing, another drone delivery logistics company out of Australia, demonstrated its product for a local member of the Australian parliament in Canberra.

What those delivery systems lack, however, is the “smart” technology that IBM designed to read an individual’s vitals and predict when they’ll need a caffeine fix. Other coffee-focused drone companies are merely semi-automated delivery guys who still rely solely on you placing the order first.

This patent enters the world just as increasingly common work perks in the tech industry such as in-office free cafeterias and gyms are being reconsidered, or at least reframed as a means for companies to keep employees working as long as possible rather than just well-meaning offerings from our corporate overlords.

Is it better that a drone use facial recognition software to detect that your eyes are drooping around 4:30 and bring you a flat white, or should we be getting our blood flowing with a quick jaunt to the local coffee shop? That’s for you and your Fitbit to decide—you still need to get your steps in, after all.

 

  • Munchies 

5 Major Tech Giants collaborate in Future of AI

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The world’s biggest technology companies are joining forces to consider the future of artificial intelligence (AI).

Amazon, Google’s DeepMind, Facebook, IBM and Microsoft will work together on issues such as privacy, safety and the collaboration between people and AI.

Dubbed the Partnership on Artificial Intelligence, it will include external experts.

One said he hoped the group would address “legitimate concerns”.

“We’ve seen a very fast development in AI over a very short period of time,” said Prof Yoshua Bengio, from the University of Montreal.

“The field brings exciting opportunities for companies and public organisations. And yet, it raises legitimate questions about the way these developments will be conducted.”

Bringing the key players together would be the “best way to ensure we all share the same values and overall objectives to serve the common good”, he added.

One notable absentee from the consortium is Apple. It has been in discussions with the group and may join the partnership “soon”, according to one member.

The group will have an equal share of corporate and non-corporate members and is in discussions with organisations such as the Association for the Advancement of Artificial Intelligence and the Allen Institute for Artificial Intelligence.

It stressed that it had no plans to “lobby government or other policy-making bodies”.

“AI has tremendous potential to improve many aspects of life, ranging from healthcare, education and manufacturing to home automation and transport and the founding members… hope to maximise this potential and ensure it benefits as many people as possible,” it said.

It will conduct research under an open licence in the following areas:

  • ethics, fairness and inclusivity
  • transparency
  • privacy and interoperability (how AI works with people)
  • trustworthiness, reliability and robustness

Microsoft’s managing director of research hailed the partnership as a “historic collaboration on AI and its influences on people and society”, while IBM’s ethics researcher Francesca Rossi said it would provide “a vital voice in the advancement of the defining technology of this century”.

Mustafa Suleyman, co-founder of Google’s artificial intelligence division, DeepMind, said he hoped the group would be able to “break down barriers for AI teams to share best practice and research ways to maximise societal benefits and tackle ethical concerns”.

And Amazon’s director of machine learning, Ralf Herbrich, said the time was ripe for such a collaboration.

“We’re in a golden age of machine learning and AI,” he said.

“As a scientific community, we are still a long way from being able to do things the way humans do things, but we’re solving unbelievably complex problems every day and making incredibly rapid progress.”

Artificial intelligence is beginning to find roles in the real world – from the basic AI used in smartphone voice assistants and web chatbots to AI agents that can take on data analysis to significant breakthroughs such as DeepMind’s victory over champion Go player Lee Sedol.

The win – in one of the world’s most complex board games – was hailed as a defining moment for AI, with experts saying it had come a decade earlier than anyone had predicted.

DeepMind now has 250 scientists at its King’s Cross headquarters, working on a variety of projects, including several tie-ins with the NHS to analyse medical records.

In a lecture at the Royal Academy of Engineering, founder Dr Demis Hassabis revealed the team was now working on creating an artificial hippocampus, an area of the brain regarded by neuroscientists as responsible for emotion, creativity, memory and other human attributes.

But as AI has developed, so have concerns about where the technology is heading.

One of the most vocal and high-profile naysayers is Tesla’s chief executive, Elon Musk, who has tweeted the technology is “potentially more dangerous than nukes [nuclear weapons]” and expressed concerns humans were “just the biological boot loader for digital super-intelligence”.

In order to combat this fear, Google are developing their own AI kill switch which will always allow humans to maintain control over AI machines.

Last year, Mr Musk set up his own non-profit AI group, OpenAI.

It is not, at this stage, part of the Partnership on AI.

If you found this article interesting, check out more similar content by visiting our latest industry news page. You can access it by following this link!

 

– Jane Wakefield

How Wimbledon will use IBM’s Watson to serve up Data

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If you’re lucky enough to get a ticket to this year’s Wimbledon tennis championships, be prepared to be scanned by a supercomputer: IBM Watson.

Cameras linked to IBM’s Watson “machine-learning” platform may be monitoring your facial expressions and trying to work out what emotions you are displaying.

If Watson learns quickly enough over the fortnight, it will apparently be able to work out which player you are supporting just by reading your face.

The All England Lawn Tennis Club (AELTC) and its tech partner IBM are remaining tight-lipped on the details of the new technology – not least because it needs legal approval and raises privacy concerns.

But it is another example of how sport is becoming increasingly digital, for fans, players and venues alike.

Even if Watson isn’t tracking your every cheer and grimace at the championships – which begin on Monday 27 June – it will be digesting millions of conversations on social media platforms, such as Twitter, Facebook and Instagram, and using natural language processing to identify common topics – not necessarily just about tennis.

“During last year’s final we were analysing about 400 tweets a second,” says IBM’s Sam Seddon. “Expand that out into Facebook, Instagram and more long-form content, and that’s a lot of data.

“We can come up with insights much faster than humans can and inform the media team so they can decide what kind of content they should be offering.”

Wimbledon’s digital team has a global audience to serve – the website received 71 million visitors last year – and a window of just a few seconds to persuade people to read its social media content rather than that of other publishers.

So, armed with IBM’s social media analysis, the team will be able to entice people chatting about their own country’s performance in the current Euro football championships, say, towards Wimbledon content about a tennis player of the same nationality.

“Social media is growing exponentially and is increasingly becoming the primary voice with which we communicate with our fans,” says Alexandra Willis, Wimbledon’s head of communications, content and digital.

Data-driven sport

On top of this social analysis by IBM’s “cognitive command centre”, sensors and computers at the venue will be collecting about 3.2 million pieces of data from 19 tennis courts across the fortnight. The tech company claims a sub-second response time and 100% accuracy.

This performance-monitoring data – everything from live scores to fastest serves to the number of backhand winners – is made available to fans via smartphone apps, the website, and now Apple TV.

You can personalise the app and receive every piece of relevant content on your favourite players, using data going back eight years.

But, to the surprise of many tech commentators, Wimbledon still has no plans to introduce wi-fi in the grounds, so visitors will have to rely on an imperfect mobile network to access all this data and content.

It will be interesting to see if this limited connectivity – and potentially higher mobile data costs – mars the user experience, particularly for international visitors.

While the tennis players can also use sensors inside tennis racquets and wristbands to monitor their own performance, under current International Tennis Federation rules the data is not allowed to be used for coaching purposes during matches.

But is there a danger players will become too reliant on detailed data analysis of their opponents and end up cancelling each other out?

“The great players know how to understand and react to what’s happening on the court – no amount of data analytics can prepare for that. It’s only one element of a sportsman’s preparation,” says Mr Seddon.

Super Bowl economics

The increased use of smartphones and apps is giving sports venues reams of valuable data about the way fans move around, the things they buy, and the content they want to watch.

For example, during February’s Super Bowl final at the Levi’s Stadium in Santa Clara, California, data analytics helped improve the fan experience and drive up sales of drinks and merchandise.

Tech firm VenueNext developed an app on behalf of the NFL (National Football League) and nearly half the stadium’s 71,000 capacity used it on the day to make purchases and access game stats.

“By offering an in-seat beverages delivery utility orders increased 67% during the Super Bowl,” says John Paul, VenueNext’s chief executive. “Delivery times averaged less than 10 minutes.”

A crack team of 200 ushers delivered the drinks and fed back data to the app on how long the queues for the toilets were, for example, and where the quickest place to buy a hotdog was at any time during the event.

“We also implemented express pick-up of merchandise after ordering online via your mobile,” says Mr Paul. “We ran out of inventory because it was so popular – we could’ve sold five times more than we did.”

The average spend was $212 (£145) and the most popular item was a woman’s Denver Broncos jacket costing $225, he says.

Horses for Courses

Mr Paul admits that the many breaks in play during an American football match make in-seat ordering practicable, but it wouldn’t be suitable for other sports and venues.

Indeed, Wimbledon’s Alexandra Willis says that’s the last thing they want during an intense tennis match. Nevertheless, location-based app data does help them improve signage and navigation for visitors across the complex site, she says.

During a summer of sport that includes the current Euro football championships, Wimbledon, and the Olympics, global audiences are set to grow and digital will be the main way most people access the action.

Andrew Chant, head of networks at cloud services firm Exponential-e, notes: “Since the Uefa European Championship began on 10 June, an average of 30% extra traffic has been added to networks.

“Excited by real-time intensity, we predict that the reach of this year’s biggest sporting events – from the Euros to Wimbledon and the Olympics – will extend far beyond the stadium and into the workplace, as connected sports fans live every second of the game, wherever they are.”

– Matthew Wall

IBM Watson: How it can be Implemented into Business

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IBM Watson and how it can be Implemented into Business

IBM is promoting its Watson natural language processing analytics technology as it tries to move its core business beyond technologies that it pioneered, but which have become commoditised. Will it fly?

In 2011, IBM’s Watson computer beat two of the most successful human contestants on the long-running US game showJeopardy!, which requires participants to provide a question in response to general knowledge clues. In the event, Watson marked a breakthrough in artificial intelligence with its understanding of natural language and ability to make sense of vast amounts of written human knowledge.

Since then, IBM has been preparing Watson for work in business, research and medicine, aiming to help organisations find answers to the questions they often ask, faster and at lower cost.

Businesses can select from a set of 28 application programming interfaces (APIs) with which they can build Watson applications, or integrate Watson’s capabilities within systems they are developing. The APIs can help analyse the tone of text, build a list of contextually related terms, script conversations and classify natural language, and are all available from IBM’s cloud platform Bluemix.

Application of these technologies is spreading. In May 2016, IBM announced a new breakthrough macromolecule that could help prevent deadly virus infections, such as Zika or Ebola, with the aid of Watson technologies. Meanwhile,global law firm Baker & Hostetler has built a ‘robot lawyer’ on Watson.

But businesses cannot simply plug in and go. Any application must first learn the ontology – the language and definitions – particular to a domain in which it operates, a process IBM will help with. From there, developers train Watson in the knowledge that makes up a particular domain, with the help of human experts in the field.

Once experts are confident in their Watson application’s ability, they can let users loose to ask it questions in natural language.

Volume, a UK-based marketing, training and technology company, has been using Watson to develop applications to help its clients in technology sales.

Chris Sykes, chief executive officer, says: “We developed bespoke software applications for enterprise clients. The idea is to create ‘cognitive consultants’ who provide accurate answers to questions from the sales teams. They are able to query in natural language in real time, making a sales person ready from day one.

“During the normal sales process, a sales person can only go so far before they need to bring in a technical expert. But if that expert is not available, it extends the sales cycle.

“With our application, the sales team have the technical knowledge they need at their fingertips. They can query the system before a meeting or while they are with the customer. Information comes back to them in natural, accurate language.

“The net benefits are higher revenue per sales person, a shorter sales cycle and higher conversion rates.”

Vast volumes of material

Applications that help businesses make sense of vast volumes of written material could benefit from using Watson, says Surya Mukherjee, senior analyst with research firm Ovum.

For example, consultancy Deloitte is working with IBM’s Watson team to offer a service that absorbs greater volumes of legal information than would be humanly possible, helping businesses save on regulatory compliance, says Mukherjee.

“Some businesses might have 20,000 pages of regulations to sift through every month to keep on top of compliance,” he says. “To understand what is relevant to them, it takes an army of lawyers. The Watson application can parse the documents, and because it knows what to look for, flag up the relevant parts.”

Crucially, Watson learns from its errors, he adds. “There are false positives and false negatives, but with heuristic algorithms and human feedback, the software learns from its mistakes over time.”

Businesses that invest in these types of application could save time and money on employing experts to analyse large volumes of text or other unstructured data – but Watson does not come cheap, says Mukherjee.

“It is not commodity technology, so it will not be commodity priced,” he says. “There will be cheques to sign.”

While users will be able to select the APIs for their applications from the cloud on a pay-as-you-go basis, they will also need to spend money to ‘train’ Watson in a particular ontology and employ human expertise to check that the applications’ output makes sense.

“You have to ask: do you have the talent to use Watson for your purpose?” says Mukherjee. “Those people are expensive, not a commodity.”

IBM is heavily promoting Watson with the term “cognitive computing”, in an attempt to move its core business beyond the technologies that it pioneered, but which have become commoditised and less profitable.

“Cognitive computing, cloud and big data are the areas where IBM is investing billions, and cognitive might just be the priority,” says Mukherjee. “In technology markets such as databases, analytics and business applications, IBM has lots of competition.

“You could say that what IBM offers, Oracle and SAP also offer. But the last frontier is cognitive, and that is IBM’s story. Tactically, it is betting the farm on Watson.”

IBM has not released pricing for Watson per se, because it will depend on the particular combination of APIs and add-on services that customers consume. It has also not announced how much it is investing in its Watson venture or discussed the computing capacity it has created to support Watson worldwide.

However, it does make strong claims about Watson’s abilities in cognitive computing.

Phil Westcott, European ecosystem leader at IBM Watson Group, says: “Watson is based on systems that learn at scale, reason with purpose and interact with humans naturally. It understands the world in the way that humans do: through senses, learning and experience.”

Elsewhere in IBM’s promotion of Watson, the company claims: “Watson and its cognitive capabilities mirror some of the key cognitive elements of human expertise: systems that reason about problems like a human does.”

Watson lacks common sense

But John Carroll, professor of computational linguistics at the University of Sussex, says that despite Watson’s impressive performance in natural language processing and question answering in Jeopardy! and elsewhere, he is sceptical about the claim that it can reason or understand the world the way humans do.

“It is different and complementary,” he says. “Humans don’t have the ability to read millions of documents an hour, so it goes beyond human ability. But, at the same time, it does not have common sense. It does not have the ability to reason inductively or understand how humans act, move and behave in the real world.

“It can do something that a human can do in same way IBM’s Deep Blue can play chess and Google AlphGo can play Go, but it is still not the answer to replicating human intelligence. It can only do the types of things it was set up to do: to get information from text and from databases and integrate them. It cannot act like a human in the real world and does not have any notion of what the real world is.”

Watson bases its responses on the expert human texts it processes, but is not able to reason much beyond this evidence, says Carroll.

“Ontologies are inconsistent and incomplete, and once you make two or three inferences, it is quite possible to go badly wrong,” he says. “The computer won’t know what is an inconsistency and what an incorrect inference is because it does not have any common sense. It can be led astray very easily. It is safer to work from documents that people have written or individual facts that people have input.”

Carroll says artificial intelligence is being applied to a range of business problems (see below) and some problems may be applicable to more specialist technologies other than Watson.

IBM has impressed businesses, academics and analysts with Watson’s performance in answering natural language questions based on vast amounts text and other unstructured data. Experts agree it has many applications that could benefit businesses and other organisations, but whether its capacity for human-like reasoning stands up to IBM’s claims remains an open question.

– Lindsay Clark

Cisco and IBM Collaborate on Internet of things Analytics

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Cisco and IBM combine edge analytics with Watson to enable a deeper understanding of data generated on the Internet of things

Cisco and IBM have begun a global collaboration to generate instant internet of things (IoT) insight at the network edge using Cisco’s edge analytics tools and IBM’s Watson IoT and business analytics technology.

Although billions of IoT devices and sensors are already generating huge amounts of data in real time, those businesses without easy access to high bandwidth connectivity to support access to the cloud have struggled to realise insight from this data, the two firms said.

Cisco and IBM believe that by joining forces, they can offer a new way of producing immediate and actionable insight at the point of data collection and can help enterprises operating on the network edge, such as manufacturing, shipping, mining and energy production, gain a deeper understanding of relevant data generated by the IoT.

“The way we experience and interact with the physical world is being transformed by the power of cloud computing and the Internet of things,” saidHarriet Green, general manager of IBM Watson IoT, commerce and education.

“For an oil rig in a remote location or a factory where critical decisions have to be taken immediately, uploading all data to the cloud is not always the best option. IBM and Cisco are taking these powerful IoT technologies the last mile, extending Watson IoT from the cloud to the edge of computer networks, helping to make these strong analytics capabilities available virtually everywhere, always.”

Mala Anaud, senior vice-president of Cisco’s data and analytics platforms group, said the collaboration would also help enterprises make better decisions based on critical data that may previously have been overlooked, or completely undetected.

“With the vast amount of data being created at the edge of the network, using existing Cisco infrastructure to perform streaming analytics is the perfect way to cost-effectively obtain real-time insights,” she said. “Our powerful technology provides customers with the flexibility to combine this edge processing with the cognitive computing power of the IBM Watson IoT platform.”

As an example, workers in underground mines may be able to monitor the health and behaviour of critical machinery and plan better for maintenance and upgrades. Cisco claimed that if they were able to adopt new approaches to condition-based maintenance, they could halve maintenance costs and increase productivity by up to 25%.

A number of tests of the collaboration have already begun in the field. In Canada, comms company Bell Canada has been using a 4G network to deliver Watson IoT and Cisco edge analytics to allow enterprise customers to collect real-time data and maximise their performance.

And in Colombia, the port of Cartagena has tapped into analytics on the edge to improve its efficiency by getting ahead of equipment degradation.

“As a container terminal trans-shipment hub, our port ships goods to almost 600 ports in 136 countries around the world,” said Eduardo Bustamante, director of operations at the port.

“The opening of the new Panama Canal has created new challenges for all ports in the region and has made service reliability a key factor of success.

“With these new capabilities from IBM and Cisco, we gain immediate insight into the health and operations of our more than 47 rubber tyre gantries and 180 trucks. As a result, we expect to be more productive in our maintenance processes to help ensure our fleet runs even more efficiently and vessels and cargo are moving smoothly in and out of the port.”

– Alex Scroxton

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