Category Archives: Ai

Advances in artificial intelligence and deep learning have changed our lives. We are already using it even without realizing it: AI helps to power Googles search engine, Teslas self-driving cars, Apples voice assistant, and Amazons shopping recommendations.

The impact of artificial intelligence in retail and ecommerce is also growing. While ecommerce giants like Amazon, Walmart, and eBay have used these capabilities behind the scenes for years, ecommerce entrepreneurs can now also do the same. Algorithmic technology and AI can be incredibly helpful tools to grow sales and optimize various aspects of ecommerce operation, from pricing to demand planning.

Here are the three most crucial applications for this tech.

Todays online retail industry is rapidly changing and presenting new challenges to ecommerce startups. The markets have become increasingly competitive, to the point where the price of each individual product must change frequently in response to market dynamics. Therefore, even for an online merchant with a couple hundred SKUs, continuous adjustment of prices quickly becomes a challenge.

Repricing merchandise strategically is particularly crucial on Amazon, where sellers constantly compete to land the Amazon Buy Box a coveted spot that essentially guarantees its winner vast sales. To select products for placement, Amazon uses sophisticated algorithms to assess merchants performance metrics such as ratings, reviews, shipping, pricing, and quality of service. For these reasons, optimal pricing of merchandise on Amazon requires sellers to go much deeper than guesstimates.

AI solves this problem by repricing merchandise using complex learning algorithms that continuously assess the market dynamics and changes in competitive environment.

Managing inventory availability across channels is one of the biggest worries for ecommerce businesses. Being out of stock is a nightmare scenario, as it takes days to replenish products and can heavily affect merchants revenues. On the other hand, overstocking increases business risks and capital requirements.

The problem with forecasting inventory velocity in a rapidly changing market is that both demand and competition change quite frequently. In such markets, a hindsight perspective traditionally implemented with the help of BI technology is no longer sufficient. In order to reach operational efficiency, retailers must employ accurate demand forecasting and predictive analytics.

Artificial intelligence and learning algorithms can help with order velocity forecasting. They can identify key factors that affect the velocity of orders, and monitor the factors impact to accurately model velocity and inventory requirements. The beauty of learning systems is that they get smarter over time, enabling merchants to accurately predict their inventory needs.

The other key aspect of retailer operation is managing the assortment of products that is, which products to keep selling, which products to add, and which products to discontinue. Like inventory planning, assortment planning requires a good amount of forecasting. Merchants need to monitor market trends and changes in demand to understand the competitiveness of products.

Although a person can analyze the past performance of products and categories, accurate forecasting requires a sophisticated algorithmic model. It must assess the relationships across products, influences of various events, and impact of competition and pricing.

Giants like Amazon and Walmart constantly monitor their product assortment and have a team of data scientists dedicated to this task. For the first time, these advanced capabilities are now available to ecommerce startups, thanks to advances in AI and algorithmic technology.

The beauty of online commerce is that it is completely digitalized. All the data from the operations, the market, and the competition can be consolidated and analyzed. It can be examined historically and now, with the help of AI technology, forecasted as well.

Now is the time for ecommerce businesses to get smarter and reach operational excellence. Logistics used to be the core competency of retail; today, algorithms constantly crunch data, predict market trends, and respond to market changes in real time. Such advancements are only possible because of AI.

Victor Rosenman is the founder and CEO of Feedvisor, an Algo-Commerce company that helps online retailers make business-critical decisions in real time.

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3 ways AI is already impacting ecommerce - VentureBeat

There appears to be a rather strange correlation between artificial intelligence and gaming right now. We have seen AIs take on players in Go, and Microsoft is now tackling the infamous Ms. Pac-Man game. Their new AI has claimed the top score in this particular game, which makes it four times better than the top-ranking human player. All of this shows us humans are not necessarily the greatest at video games, unfortunately.

It is not entirely surprising to learn artificial intelligence solutions are better at playing particular video games compared to most humans. After all, we humans are great at doing several things quite well, whereas an AI can excel at doing just one thing better than anything else. In this particular case, Microsofts new AI has thrashed all human players when it comes to Ms. Pac-Man, as it successfully reached the top score possible. An impressive feat, although some people may not be too happy about it.

To put this news into perspective, reaching the top score in Ms. Pac-Man is no easy feat, not even for an AI. In fact, experts felt his particular game is the hardest to beat for an artificial intelligence. There is a lot going on at the same time, and the circumstances of the game can shift around quite a bit. Interestingly enough, Microsofts concoction was more than capable of handling the pressure and made playing the game look like a walk in the park.

The AI in question is developed by Maluuba, a Canadian deep learning startup owned by Microsoft. The company was acquired earlier in 2017, and it appears Microsoft has made a smart move in doing so. Beating the Ms. Pac-Man game is the companys first major feat, but it certainly is one that will go down in the history books. In comparison, the best human player to date scored four times fewer points in the game.

Under the hood, the AI used a method described as Hybrid Reward Architecture. It is a combination of reinforcement learning algorithms. By training around 150 individual AI agents to work together in parallel, the team successfully ensured its creation could reach the top score. All agents were rewarded for eating pellets, whereas others were trained to avoid ghosts. Combining all of these experiences into one project lead to this unexpected success.

The world of video games is slowly being dominated by artificial intelligence these days. Googles AlphaGothrashed the world champion not too long ago and promptly announced retirement. Now that Microsofts project has beaten Ms. Pac-Man, it is doubtful the AI will play this game ever again. Once the maximum result is achieved, there is no reason for these AI creations to keep playing the same game, as there is no further room for significant improvement.

The fact an AI can defeat a rather unpredictable game with such ease is rather telling, though. It is evident artificial intelligence is incredibly powerful at this stage, at least where these single-player games are concerned. It will take some time until we see an AI be successful in competitive multiplayer games, though, but it may happen at some point.

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Microsoft's New AI Reaches High Score in Ms. Pac-Man - The Merkle

TechCrunch

A discussion about AI's conflicts and challenges TechCrunch He's now research director at the Alan Turing Institute in the UK, which aims to support data science research, which of course means machine learning and AI, and includes probing the ethics and societal implications of AI and big data. So how can a ...

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A discussion about AI's conflicts and challenges - TechCrunch

In Brief While developing negotiating chatbot agents, Facebook researchers found that the bots spontaneously developed their own non-human language as they improved their techniques, highlighting how little we still know about how artificial intelligences learn. The Future of Language

A recent Facebook report on the way chatbots converse with each other has given the world a glimpse intothe future of language.

In the report, researchers from the Facebook Artificial Intelligence Research lab (FAIR) describe training their chatbot dialog agents to negotiate using machine learning. The chatbots were eager and successful dealmaking pupils, but the researchers eventually realized they needed to tweak their model because the bots were creating their own negotiation language, diverting from human languages.

To put it another way, when they used a model that allowed the chatbots to converse freely, using machine learning to incrementally improve their conversational negotiation strategies as they chatted, the bots eventually created and used their own non-human language.

The unique, spontaneous development of a non-human language was probably the most baffling and thrilling development for the researchers, but it wasnt the only one. The chatbots also proved to be smart about negotiating and used advanced strategies to improve their outcomes. For example, a bot might pretend to be interested in something that had no value to it in order to be able to sacrifice that thing later as part of a compromise.

Although Facebooks bargain-hunting bots arent a sign of an imminent singularity or anything even approaching that level of sophistication they are significant, in part because they prove once again that an important realm we once assumed was solely the domain of humans, language, is definitely a shared space. This discovery also highlights how much we still dont know about the ways that artificial intelligences (AIs) think and learn, even when we create them and model them after ourselves.

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A Facebook AI Unexpectedly Created Its Own Unique Language - Futurism

Intel and Microsoft have been on something of an artificial intelligence (AI) investment binge of late, with the chip and software giants announcing a slew of deals this week via their respective VC arms Intel Capital and Microsoft Ventures.

Perhaps the most notable of these was Element AI, which raised a gargantuan $102 million in what is one of the largest series A rounds in recent times. The Montreal-based startup, which helpsconnect companies with machine learning experts, drew in some other interesting investors besides Intel and Microsoft, including rival chipmaker Nvidia.

The Element AI deal followed just a day afterIntel and Microsoft joined forcesfor a $15 million investment into CognitiveScale, a Texas-based startup that uses AI to harness big data and deliver insights and recommendations. The very same day, Intel participated in a $16 million round into California-based robotic vision startup Aeye, while on Monday Microsoft got involved in a $20 million funding round into CrowdFlower, a platform that meshes machines with human input to ensure data science teams have access to properly tagged, clean data. Microsoft also invested in in CrowdFlower last year.

The duo have been investing in AI-related startups all year, too.

Back in January, Intel Capitaljoined a $14 million funding round into Mighty AI, astartup that uses the general public to help train companies AI algorithms, and a $7 million round into cybersecurity startupFortscale, which uses machine learning and big data analytics to detect malicious user behavior. But the most sizeable deal to emerge from Intel this year so far was its $15 billion acquisition of Mobileye, a computer vision firm specializing in autonomous cars.

Last month, Microsoft Ventures revealed it had contributed to a $3.5 million seed round intoNew York-based Agolo, a startup thats setting out to help companiesfight information overload through AI-powered summarizations. And on the same day, Microsoft Ventures announced it was also leading a $7.6 million round into Bonsai, a startup that helps companies build AI into their business.

As with Intel, Microsoft has also made some AI acquisitions this year. Last week, itacquired Israeli startup Hexadite to bring AI-powered security to Windows 10 in the enterprise, while back in January it boughtresearch-oriented deep learning startup Maluuba.

All the major tech titans, from Alphabet and Amazon through to Apple and beyond, have made AI acquisitions in recent times, but the recent flurry over the past week indicates the talent land grab is intensifying. Indeed, Microsoft recently launched a dedicated fund for AI startups, while Intel Capital alone now claims more than 25 AI companies in its portfolio.

As we proceed toward realizing the promise and opportunity offered by AI, Intel is aggressively investing in the best minds in the industry that bring the skills and technology necessary to accelerate complex, data-intensive processes, Intel said in a statement issued to VentureBeat. Each of these companies is involved in furthering innovations with AI ranging from robotics and autonomous vehicles to machine intelligence software and an AI research lab with the premise of solving our most daunting challenges by accelerating large-scale problem-solving, unleashing new scientific discovery, extending our human senses and capabilities, and relieving us of the burden of tedious or dangerous tasks.

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Intel and Microsoft's latest investment binge shows AI land grab is intensifying - VentureBeat

BBC News

Garry Kasparov: Why the world should embrace AI BBC News Will it actually be, though? Not at all, says chess grandmaster and former World Chess Champion Garry Kasparov. Kasparov has direct experience of being humbled by a machine, so it's perhaps surprising that he has a pro-AI outlook. In the 1990s, the ... and more »

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Garry Kasparov: Why the world should embrace AI - BBC News

Daily Report: The Limits of AI New York Times Facebook, under pressure in a number of countries because of criticism that it is not doing enough to curtail extremist content on its site, says it is going to lean on artificial-intelligence technology in its response to the problem, Sheera Frenkel ...

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Daily Report: The Limits of AI - New York Times

Not long ago, we saw how no less than Elon Musk was concerned about the state of artificial intelligence (AI), and was working to try and make it so it didn't destroy the world when it came out. New research from Gallup, meanwhile, suggests that Musk may actually have something to worry about, or rather, millennials do. AI may be more of a threat to future employment than a lot of people realize right now, especially as relates to millennials.

The Gallup report notes that AI, along with automation, are some of the most disruptive forces the workplace has ever seen, and fully 37 percent of millennials are at high risk of being replaced by one of these two. The two older generations, boomers and Generation X, are only slightly less at risk, with about 32 percent risk.

The slight drop-off in risk comes from the slightly increased likelihood that older workers hold managerial positions, which are less likely to be hit by AI and automation systems. Younger workers commonly have fewer skills, and lower-skill positions are more likely to be automated.

While there's some doubt over just how long the changeover will takesome think years, others decadesit's already been shown that companies are already at least partially tech firms now. Most every company, from retailers to healthcare firms, has a Web presence, a mobile presence, and all the like; it's part of the push to omnichannel.

Thus, many are starting to think, how long before an AI is put in charge of all of that and most every human let go? It's not out of line to think that way; the basic precepts of capitalism say that, if it's possible for a business to save money, it needs to do so. If it doesn't, it risks falling behind competitors who will do so, and inevitably closing anyway. Some suggest potentially impacted employees take on a more entrepreneurial look at life or focus on retraining; even these are only partial addresses.

What retraining and entrepreneurial advocates seem to forget is that these things require working markets to function. If large portions of the populationlike that 37 percentcan't find work, those portions aren't buying things. If they aren't buying, the market is reduced by that same percentage. Industries would do well to realize that AI systems don't shop; what happens to the companies that produce these things, even if they do the right thing and fire everybody for AI replacements? It's a false savings that will ultimately mean shuttered businesses. Will anyone realize that before sending out the pink slips? That's an uncertain conclusion at best.

Edited by Alicia Young

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AI Systems Increasingly Taking Jobs from Millennials - Techzone360

TechCrunch

Entelo steps up its AI game with $20M Series C TechCrunch The race to crown a winner in the AI-powered recruiting software space is on. With both Workey and Mya nabbing rounds in the last few weeks, the timing is prime for a few players to seek advantage in the form of growth capital. This seems to be exactly ... and more »

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Entelo steps up its AI game with $20M Series C - TechCrunch

TechCrunch

Microsoft's AI beats Ms. Pac-Man TechCrunch As with so many things in the world, the key to cracking Ms. Pac-Man is team work and a bit of positive reinforcement. That and access to funding from Microsoft and 150-plus artificial intelligence agents as Maluuba can now attest. Last month, the ... Microsoft AI plays a perfect game of Ms Pac-ManBBC News Microsoft AI gets maximum score possible on Ms. Pac-ManCNET Sorry humans, Microsoft's AI is the first to reach a perfect Ms. Pac-Man scoreThe Verge Quartz -New Atlas -The Official Microsoft Blog - Microsoft -YouTube all 79 news articles »

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Microsoft's AI beats Ms. Pac-Man - TechCrunch