Prateek Joshi is an artificial intelligence researcher, published author of five books, and TEDx speaker. He is the founder of Pluto AI, a venture-funded Silicon Valley startup building an analytics platform for smart water management powered by deep learning. His work in this field has led to patents, tech demos, and research papers at major IEEE conferences. He has been an invited speaker at technology and entrepreneurship conferences including TEDx, AT&T Foundry, Silicon Valley Deep Learning, and Open Silicon Valley. Prateek has also been featured as a guest author in prominent tech magazines.

Many of us have recalled the definition of insanity when experiencing frustration at work. After all, doing the same thing over and over again and expecting a different result doesn't make any sense. This is one way to think about recent developments in Artificial Intelligence, or AI. It helps you get different, better results. Without getting technical, at best, in the past companies developed analytics based on assumptions and historical information.

Tesla and SpaceX CEO Elon Musk is renowned for making dire predictions about how artificial intelligence will be a threat to humankind. While it's not yet self-evolving to the point of being an imminent danger, in 2017 AI did grow like crazy. At least that's the topic several CEOs wanted to mention when asked what they saw as the biggest trends in tech this year. "Automation and artificial intelligence (AI) have a symbiotic relationship and pose both a blessing and a threat to the future of commerce. With innovations in data mining and automation, the ability for large companies to mine data is vastly improving. This is creating a shift from helpful automation towards immersed AI and immense amounts of data are fueling predictive consumerism that furthers the ability for large corporations to accurately predict and recommend products, shaping consumer habits. This paves the way for traditional verticals of commerce and manufacturing to dissolve, and large data aggregators move directly into manufacturing. "Social listening provides brands with a bird's eye view of trending topics, sentiment and conversations related to their industry, products and public perception.

By 2019, about 40% of retailers will develop a customer experience architecture supported by artificial intelligence, with such platforms providing up to a 30% conversion increase and a 25% revenue bump due to hyper-micro personalization, according to IDC Retail Insights' list of 10 retail predictions. Among other predictions, IDC speculated that by 2021 10% of chain retail sales will be created and managed via voice-enabled digital assistants, which will accelerate the predominance of marketplaces for buying everyday goods. Also, in the midst of rapidly evolving cyberthreats, 75% of retailers are expected to adopt AI-based cyber-defense technologies by 2020, according to IDC. AI is mentioned repeatedly in IDC's predictions, and for good reason. AI and voice-driven virtual assistants have already shaken up the retail scene in a number of ways, so the notion that they will now redefine things like customer experience and cybersecurity isn't coming out of left field.

As big data and artificial intelligence continue to spread their gargantuan influence throughout the global economy, today's investors and tech entrepreneurs eager to make a buck off of these innovations in 2018 are starting to identify the key trends that will come to define them. So, what exactly are the driving forces behind today's artificial intelligence and big data boom, and what can eager investors looking to cash in on this phenomenon do to prepare themselves? As it turns out, many of the forces that have defined the AI revolution thus far are still at work, and will continue to define how AI impacts the markets well into 2018. By familiarizing yourself with these top 5 emerging trends, you and your company will be well-prepared to leverage big data and AI-based solutions as the new year approaches. Few areas stand to benefit as much from the recent boom in big data and artificial intelligence as AI; whether it's Walmart or your local mom and pop shop, businesses everywhere seem to be leveraging these technologies to cut their overhead cost while widening the scopes of their business.

Machine Learning is a pivotal technology for many startups and enterprises. Despite decades of investment and improvements, the process of developing, training, and maintaining machine learning models has still been cumbersome and ad-hoc. The process of incorporating machine learning into an application often involves a team of experts tuning and tinkering for months with inconsistent setups. Businesses and developers want an end-to-end, development to production pipeline for machine learning. Amazon SageMaker is a fully managed end-to-end machine learning service that enables data scientists, developers, and machine learning experts to quickly build, train, and host machine learning models at scale.

Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning. Machine learning often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow. First, you need to collect and prepare your training data to discover which elements of your data set are important. Then, you need to select which algorithm and framework you'll use.

LAS VEGAS -- Amazon Web Services unveiled its latest wares in the cloud-computing arms race here on Wednesday, deploying a suite of services designed to let software developers take advantage of artificial intelligence capabilities without first getting a Ph.D. Andy Jassy, chief executive of the online retailer's cloud-computing unit, announced more than a dozen new services, including software that translates and transcribes speech, analyzes videos and gives developers a leg up in building their own tools. He was speaking in a keynote Wednesday morning at AWS's sixth annual re:Invent conference. "The hype and the hope here is tremendous," Jassy said of machine learning, the set of services that helps algorithms improve with experience. Many companies are experimenting with such services, he said, "yet I would argue it's still very early." Jassy's unit, Amazon's most profitable division, grew up by offering bite-sized, simple services: storage and computing power, at first, and later, database tools and other on-demand versions of existing business software.

Amazon.com Inc wants to be your new executive assistant at work. The company on Thursday said that Alexa, its increasingly popular digital aide that shoppers command by voice, is now programmed to handle a range of tedious office tasks. Businesses can buy Alexa devices that help employees dial into conference calls, manage their calendars, find open meeting rooms and - not surprisingly - order work supplies from Amazon. Amazon is looking to make money in the long term from people shopping with Alexa and using it - rather than Apple Inc's Siri or Alphabet Inc's Google Assistant - as their go-to voice technology Amazon wants Alexa to be everywhere, and it needs more voice data to feed and'train' it so that talking to the assistant feels like talking to a friend. The company is looking to make money in the long term from people shopping with Alexa and using it - rather than Apple Inc's Siri or Alphabet Inc's Google Assistant - as their go-to voice technology.