This is the first of a four part series on machine learning and deep learning written for AI Trends by Piotr Migdal, Ph.D., deepsense.ai. Every time you watch a film Netflix has suggested or buy a “similar product” on Amazon, it is a personalized recommendation. Can you make such recommendations work for your business as […]
The world of artificial intelligence is frightening. No, not the danger of an army of AI-powered robots taking over the world (though that is a bit concerning). The real fear is that the wrong vendor is chosen or the rollout handled poorly. After all, AI is complex, not fully mature, in some cases poorly understood, and […]
There are about 7.5 billion people on the planet, give or take a few. But that number pales in comparison to the number of connected devices worldwide. According to Autonomous, a financial research firm, people are outnumbered three-to-one by their smart computing devices — an estimated 22 billion in total. And the number of smart devices will […]
According to a McKinsey report, only 20% of companies consider themselves adopters of AI technology while 41% remain uncertain about the benefits that AI provides. Considering the cost of implementing AI and the organizational challenges that come with it, it’s no surprise that smart companies seek ways to test the solutions before implementing them and get […]
By Lance Eliot, the AI Trends Insider How do you learn something? That’s the same question that we need to ask when trying to achieve Machine Learning (ML). In what way can we undertake “learning” for a computer and seek to “teach” the system to do things of an intelligent nature. That’s a holy grail […]
Forbes |
Why Training Machine Learning With Multitenant Data Produces Better Results
Forbes There is a simple rule with machine learning: The more data available to train the machine, the smarter the machine becomes. I can relate with an example I’m sure is familiar to all of us. Remember iTunes “Smart” Playlists? It was a cool way to give … |
ZDNet |
The AI, machine learning, and data science conundrum: Who will manage the algorithms?
ZDNet Artificial intelligence and machine learning are being adopted into the enterprise at a rapid clip and adoption is likely to surge in 2019. What comes next is the real business challenge: How will we manage technology that we likely don’t understand? |
Design and Reuse (press release) |
Optimizing AI and Machine Learning with eFPGAs
Design and Reuse (press release) The market for artificial intelligence (AI) and machine learning applications has been growing substantially over the last several years. Designers have a tough row to hoe when it comes to satisfying these applications’ seemingly insatiable compute hunger. |
New Open-Source Projects Emerge for Machine LearningDatanamiTwo open-source projects contributed by Chinese tech giants Baidu and Tencent will focus on machine and deep learning advances with the long-term goal of making the AI technologies easier to u…
Wall Street Journal (blog)SAP Bets Machine Learning Can Make Workplace More TransparentWall Street Journal (blog)Software and technology services vendor SAP SE wants to help managers improve their leadership skills and retain employees by launching abo…
