Tag: artificial intelligence

By Lisa Du and Ayaka Maki for Bloomberg/Fin24

It’s watching, and knows a crime is about to take place before it happens.

Vaak, a Japanese startup, has developed artificial intelligence software that hunts for potential shoplifters, using footage from security cameras for fidgeting, restlessness and other potentially suspicious body language.

While AI is usually envisioned as a smart personal assistant or self-driving car, it turns out the technology is pretty good at spotting nefarious behaviour. Like a scene out of the movie “Minority Report,” algorithms analyse security-camera footage and alert staff about potential thieves via a smartphone app.

The goal is prevention; if the target is approached and asked if they need help, there’s a good chance the theft never happens.

Vaak made headlines last year when it helped to nab a shoplifter at a convenience store in Yokohama. Vaak had set up its software in the shop as a test case, which picked up on previously undetected shoplifting activity. The perpetrator was arrested a few days later.

“I thought then, ‘Ah, at last!’” said Vaak founder Ryo Tanaka, 30. “We took an important step closer to a society where crime can be prevented with AI.”

Shoplifting cost the global retail industry about $34bn in lost sales in 2017 – the biggest source of shrinkage, according to a report from Tyco Retail Solutions. While that amounts to approximately 2% of revenue, it can make a huge difference in an industry known for razor-thin margins.

The opportunity is huge. Retailers are projected to invest $200bn in new technology this year, according to Gartner, as they become more open to embracing technology to meet consumer needs, as well as improve bottom lines.

“If we go into many retailers whether in the US or UK, there are very often going to be CCTV cameras or some form of cameras within the store operation,” said Thomas O’Connor, a retail analyst at Gartner. “That’s being leveraged by linking it to an analytics tool, which can then do the actual analysis in a more efficient and effective way.”

Because it involves security, retailers have asked AI-software suppliers such as Vaak and London-based Third Eye not to disclose their use of the anti-shoplifting systems. It’s safe to assume, however, that several big-name store chains in Japan have deployed the technology in some form or another.

READ: Amazon facial AI matched politicians with criminals in test
Vaak has met with or been approached by the biggest publicly traded convenience-store and drugstore chains in Japan, according to Tanaka.

Big retailers have already been adopting AI technology to help them do business. Apart from inventory management, delivery optimisation and other enterprise needs, AI algorithms run customer-support chatbots on websites. Image and video analysis is also being deployed, such as Amazon.com’s Echo Look, which gives users fashion advice.

“We’re still just discovering all the market potential,” Tanaka said. “We want to keep expanding the scope of the company.”

Founded in 2017, Vaak is currently testing in a few dozen stores in the Tokyo area. The company began selling a market-ready version of its shoplifting-detection software this month, and is aiming to be in 100 000 stores across Japan in three years. It has ¥50m ($450 000) in funding from SoftBank Group’s AI fund, and is in the middle of its series A round, seeking to raise ¥1bn.

What makes AI-based shoplifting detection a straightforward proposition is the fact that most of the hardware – security cameras – is usually already in place.

READ: Microsoft seeks to restrict abuse of its facial recognition AI
“Essentially this is using something that’s been underutilised for decades,” said Vera Merkatz, business development manager at Third Eye. Founded in 2016, the startup offers services similar to Vaak in the UK market, where it has a deal with a major grocery chain. Third Eye is looking to expand into Europe.

The ability to detect and analyse unusual human behaviour also has other applications. Vaak is developing a video-based self-checkout system, and wants to use the videos to collect information on how consumers interact with items in the store to help shops display products more effectively.

Beyond retail, Tanaka envisions using the video software in public spaces and train platforms to detect suspicious behavior or suicide jumpers. At Third Eye, Merkatz said she’s been approached by security management companies looking to leverage their AI technology.

“The potential is broad since it can be applied outside of shoplifting prevention and outside of retail — such as with manufacturing or other types of marketing,” said Hiroaki Ando, a retail consultant at Ernst & Young Advisory & Consulting in Tokyo.

The “humAIns” are coming

By Sudipto Ghosh for MarTechSeries

According to the latest Accenture report on the future of workplace collaborations, businesses that manage to balance human ingenuity with machine intelligence will be successful. Released just ahead of the World Economic Forum 2018 in Davos, Accenture’s AI report takes a positive stance on the need to grow investments into AI and Human-Machine collaboration over the next five years.

So, what can we expect at such a ‘modern’ workplace?

Let’s call the new professionals that you could be hiring and collaborating with, by 2022 “the humAIns”.

Who are humAIns?

HumAIns are machine-driven, human-centric workplace assistants that demonstrate the highest ability to deliver “Live” customer experiences. No biases, even with millions of insights to deal with from historical data, the HumAIns will boost three aspects of any business:

  • Increase revenues
  • Maximise profits
  • Guarantee human employment with respectable salaries

According to the Accenture report on AI-Human collaboration, the HumAIns could boost revenues by 38% and grow employment opportunities by 10 percent between 2018 and 2022.

The convergence of AI and the human race within economic circles
The HumAIns (no more a hypothesis), would propel the adoption of technology across industries. The economic fields of study for AI would expand further into these five categories:

  • Deep Learning: Synchronous group of machines running on powerful algorithms led by a human expert.
  • Robotization: Machines take over humans, freeing the creative minds to focus on refining business strategies.
  • Dematerialization: Voice search, intelligent assistants, automatic streaming tools, and contactless payment solutions.
  • In-app Workforce; Employees share their availability and managers delegate tasks via apps, also part of Gig economy and crowd-working.
  • Autonomous Operations: Driving tech, sensor technologies, IoT, and drones powered by AR/VR, turning into the norm.

Humanisation of technology

Almost all first-world countries are prepared for the “Fourth Industrial Revolution”. For example, the Netherlands became the first country to set up a nationwide internet of things network. With this move, The Netherlands has enabled the connection of more intelligent devices than it has inhabitants.

“Go digital. Use VR, AR and Al to accelerate the speed and scale of effective training.” – Accenture, Reworking The Revolution

While the cost of employment is a chief reason why developed countries are seeking smarter technologies to replace humans, growing economies like India, China, and Bangladesh still benefit from the availability of low-cost, medium-skilled workers in all industrial sectors.

As all countries grow in terms of industrial parity, employment standards would also incline majorly towards robotization, automation, and dematerialization. This opens up a new horizon for HumAIns to make their presence felt.

HumAIns would hire people for their skills and not for their personal choices. The intelligent assistants would manage the entire value chain of man, machine, material, money, and to an extent, mind too.

The Darker Side: HumAIns Crack the Whip on ‘Dark’ Data Science

Most businesses have a sense of what Big Data is. But analyzing ‘unstructured’ data is still a mystery (something with no label of what data-type it is, or what family it belongs to — not even the source)! HumAIns, taking a cue from the Apple-Lattice Data amalgamation, or from the newest in the market, Vyasa Analytics, could enable the machine’s “cortex” to ask pertinent questions on the ‘Who-What-Where-When-How’ in analyzing Dark Data.

For HumAIns, the power of collaborative analytics in Dark Data would open new fields of opportunities across the verticals and horizontals in business. A large part of that would benefit how CMOs zero in on their tech stack.

HumAIns in B2B Technology: A Cool Angle to Working with Machines

HumAIns would erase the need for having human supervision for the common marketing activities, that mostly deal with interactions and problem-solving at all stages of operations. The activities are:

  • Customer Targeting and Retargeting
  • Media Buying
  • Cross-channel Marketing Executions
  • Testing, Optimization, and Personalization
  • Analytics and Insights

For a CMO working with a HumAIn, the foreseeable benefits could include:

  • Savings in time, money, and human resources
  • Unbiased collaboration 24/7/365
  • More accurate, quicker, and justifiable investment decisions
  • Competitive intelligence with clear focus on revenue acceleration
  • Uncompromising and unending repository of intelligence and measurable emotion into marketing and advertising
  • Delightful customer experiences with the highest return on personalization
  • Higher-value in problem-solving with real-time historical references to common challenges in marketing

Will AI take away jobs? Certainly not, if you know how to collaborate with the HumAIns. Trusting what Accenture report suggests, “Foster a new leadership DNA. Cultivate leaders at all levels to help pivot the workforce to new growth models.” What part of that DNA would match up to HumAIns? Interesting thought, isn’t it?

Automation could kill 800m jobs worldwide

As many as 800-million workers worldwide may lose their jobs to robots and automation by 2030, equivalent to more than a fifth of today’s global labour force.

That’s according to a new report covering 46 nations and more than 800 occupations by the research arm of McKinsey & Co.

The consulting company said on Wednesday that both developed and emerging countries will be impacted. Machine operators, fast-food workers and back-office employees are among those who will be most affected if automation spreads quickly through the workplace.

Even if the rise of robots is less rapid, some 400-million workers could still find themselves displaced by automation and would need to find new jobs over the next 13 years, the McKinsey Global Institute study found.

The good news for those displaced is that there will be jobs for them to transition into, although in many cases they’re going to have to learn new skills to do the work. Those jobs will include health-care providers for aging populations, technology specialists and even gardeners, according to the report.

“We’re all going to have to change and learn how to do new things over time,” Michael Chui, a San Francisco-based partner at the institute, said in an interview.

Reported by Rich Miller for Bloomberg LP on Tech Central

Staples is ready to test a technology that lets companies order office supplies by voice. Developers and e-commerce experts at the company worked with International Business Machine’s Watson artificial intelligence system to build the Easy System, which Staples expects to test with customers before the end of the year.

The retailer joins a range of large companies, including Facebook, Automatic Data Processing, and Humana, using AI to build intelligent software agents that understand natural language and field multifaceted requests. Some see bots as the next user interface beyond swiping and clicking. Staples, for example, wants to let business customers order supplies that it may not carry, offering to find and deliver such products, says Faisal Masud, executive vice president of global e-commerce at the office supply retailer.

The Easy System users initiate by pressing a red “easy” button is designed to learn with each interaction, says Masud. The cognitive computing scheme behind Watson lets Staples’ algorithms learn the habits of individual customers. Eventually, for example, the system will understand that a customer’s reference to “blue pens” means an 18-pack of Pentel ballpoints.

Staples uses application programming interfaces to connect its inventory and ordering systems to Watson, via IBM cloud technology. The system checks contracts and business processes set up for each customer, to ensure an order meets appropriate approvals, he says.

If an order exceeds a spending threshold, for example, it could be routed by text or email to a supervisor for an override. If there’s an issue the Easy System can’t resolve, it will automatically invoke a live link to a human customer service agent.

“We want to become the right-hand for the office administrator,” says Masud.

By Kim S Nash for www.blogs.wsj.com

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