If you're one of the 4.5 billion people connected to the internet today, you use a search engine to find, purchase, or learn about pretty much anything that comes to mind. Consumer search engines provide a seamless way for us to make sense of our complex world. And consumers are used to a search experience that is fast, accurate, and constantly improving. But when those same people try to search within their CRM at work, the experience is painfully underwhelming: too many clicks to find what you're looking for and an interface that confuses more than it helps. This shouldn't be the case today.
The AI and ML deployments are well underway, but for CXOs the biggest issue will be managing these initiatives, and figuring out where the data science team fits in and what algorithms to buy versus build. Pure Storage launched a bevy of artificial intelligence tools, including the AI Data Hub, which are designed to meld storage and AI workflows from design to deployment. The storage company said it co-developed the AI Data Hub with Nvidia to break down the data silos that hamper analytics and model development. Storage vendors have been increasingly focused on AI workloads and managing data workflows instead of just storing it. Pure has been using its AI-Ready Infrastructure (AIRI) and expertise in solid-state storage via its Flashblade infrastructure to grab next-gen workloads.
Every day, there is a new report, news item, scientific publication where some company or the other, some research team, some start up claims to have launched a product built with Artificial Intelligence, or to have achieved a breakthrough in this field, or promises a new product which will change the entire field. Unfortunately, the term Artificial Intelligence or AI for short, has to be the most over abused term by scientists, computer programmers, start up entrepreneurs and the tech media alike. It is still in close competition with the term Big Data, though. My name is Sukhbir Benipal and i am the founder and creator of the e commerce search engine benipal.com, I have been working in this field for over 5 years and tried endlessly, at various points even believing i had a breakthrough, until one day when Hurricane Sandy hit Manhattan, and with no power, heat or running hot water, finally realizing i was so wrong, on all counts.
Expedia Group has announced a collaboration with AI Singapore (AISG) – an inter-agency unit tasked to catalyse and grow the country's artificial intelligence (AI) capabilities – under its flagship 100 Experiments (100E) programme to develop an AI solution to transform the online search experience for Asian travellers. The first online travel platform to collaborate with AISG for 100E, Expedia Group will provide a team of experienced engineers, data scientists and marketers to work with the AISG's project lead, project managers and AI apprentices to enhance travel search query understanding and improve the accuracy of search query resolution in Asian languages. Today's search engines are efficient in understanding travel search queries and providing query resolutions in English, as English is the dominant language used online by 25 per cent of all Internet users. However, when dealing with travel search queries conducted in Asian languages such as Japanese, Korean, simplified Chinese and traditional Chinese, the performance of the search engines declines significantly and the accuracy of query resolution dips. For a start, the Expedia Group and AI Singapore project team will leverage natural language processing and machine learning to develop an AI-based model to enhance search query understanding and resolution in the Japanese language, before extending the model to other Asian languages to enhance online search efficiency.
It's the year 2019--and the rise of the machines is transforming digital marketing. Nowadays, AI makes it much easier to generate information for online shoppers directly from a website or in the search results. Yes, that horror movie recommended in your streaming library is generated from AI. Artificial intelligence can both generate and curate content to personalize the user experience. The system is able to generate content based on matching data and information that has been indexed through the internet. For instance, you may notice this as a pop-up that appears as soon as a user visits your website.
This article broadly describes the capabilities that constitute an enterprise analytics program or competency. The intention initially, was to provide tips on mitigating challenges encountered in implementing an analytics practice - but that is going to be relegated to a future article. IT projects in general, and analytics projects, in particular, are notoriously unsuccessful or "challenged". Focusing attention on the following short list prior to embarking on an analytics project or enterprise will help mitigate many challenges and obstacles encountered when delivering value through analytics projects. These outcomes are dependent on several factors, and achieving them requires implementing and orchestrating some, or all of the following core capabilities listed below.
RTIH rounds up the retail technology startups who have been making waves with major investments. Syte, an Israeli artificial intelligence tech startup that powers visual search for the likes of M&S and boohoo, has raised $21.5 million in a Series B round led by Viola Ventures. Smart grocery cart startup Caper has closed a $10 million Series A led by Lux Capital. The round also saw participation from First Round Capital, Y Combinator, Hardware Club, FundersClub, Sidekick Fund and Red Apple Group. Akeneo, a US-based SaaS venture that provides product information management solutions for omnichannel retailers and brands, has raised $46 million in a funding round led by Summit Partners.
In 2015, The Allen Institute for Artificial Intelligence -- the research organization founded by late Microsoft cofounder Paul Allen -- released Semantic Scholar, a public AI search engine capable extracting figures from over 173 million computer science and biomedicine journal papers. It received a warm reception, but researchers at the Institute wondered if its underlying algorithms might be adapted to solve other problems in the field of medical research. To this end, the Allen Institute this week launched Supp AI, a web portal that lets consumers of supplements like vitamins, minerals, enzymes, and hormones identify the products or pharmaceutical drugs with which they might adversely interact. Using a no-frills search bar, they're able to type in trade names for common drugs (e.g., Prozac and Sarafem) and names of active drug ingredients (fluoxetine) to bubble up sentences from research papers supporting interactions alongside links to each source. Supp AI not only surfaces all chemicals or drugs that might interact with a queried supplement, but it helpfully sorts the evidence sentences and prioritizes source papers based on associated metadata.
What is your hospital currently spending on overhead costs? Chances are it's closer to 25%. According to a study by The Commonwealth Fund, administrative costs account for 25.3% of hospitals budgets. This is money that does not typically improve patient care, but rather is associated with IT, scheduling or billing. There are multiple ways to reduce these costs by using different AI or IoT methodologies.
Despite the age of big data, 71% of organisations still rely on a single data source to analyse asset performance and risk management – instead of drawing information from multiple sources for a more comprehensive view, reveals a report released by Lloyd's Register at Gastech today. The report, 'Oil & Gas: Achieving operational excellence in uncertain times' reveals the technologies US oil and gas companies currently use to manage and maintain their assets, and the methods they plan to adopt in the future. Tim Bisley, SVP, Software at Lloyd's Register commented: "Although organisations often collect vast amounts of data, they remain challenged as to how to use it. Predictive maintenance is reaching new levels thanks to AI, 3D digital twins and machine learning, which derive actionable insights from huge volumes of data. The report, however, indicates the industry has been slow to adopt this type of technology, in spite of the efficiencies it brings."