Microsoft buys conversational AI company Semantic Machines for an undisclosed sum

Microsoft announced it has acquired Semantic Machines, a conversational AI startup providing chatbots and AI chat apps founded in 2014 having $20.9 million in funding from investors. The acquisition will help Microsoft catch up with Amazon Alexa, though the latter is more focused on enabling consumer applications of conversational AI.

Microsoft will use Semantic Machine’s acquisition to establish a conversational AI center of excellence in Berkeley to help it innovate in natural language interfaces.

Microsoft has been stepping up its products in conversational AI. It launched the digital assistant Cortana in 2015, as well as social chatbots like XiaoIce. The latest acquisition can help Microsoft beef up its ‘enterprise AI’ offerings.

As the use of NLP (natural language processing) increases in IoT products and services, more startups are getting traction from investors and established players. In June last year, Josh.ai, avoice-controlled home automation software has raised $8M.

Followed by it was SparkCognition that raised $32.5M Series B for its NLP-based threat intelligence platform.

It appears Microsoft’s acquisition of Semantic Machines was motivated by the latter’s strong AI team. The team includes technology entrepreneur Daniel Roth who sold his previous startups Voice Signal Technologies and Shaser BioScience for $300M and $100M respectively. Other team members include Stanford AI Professor Percy Liang, developer of Google Assistant Core AI technology and former Apple chief speech scientist Larry Gillick.

“Combining Semantic Machines’ technology with Microsoft’s own AI advances, we aim to deliver powerful, natural and more productive user experiences that will take conversational computing to a new level.” David Ku, chief technology officer of Microsoft AI & Research.

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ADLINK Launches IoT Digital eXperiments-as-a-Service to Alleviate High Costs and Risks

By A.R. Guess

A recent press release states, “ADLINK Technology has announced the launch of its innovative DXS IoT digital experiments as-a-service offering. The service is for the testing of potential IoT-based endeavours to determine the viability of possible solutions with none of the upfront costs and risk associated with a full solution commitment. Full IoT solutions conventionally […]

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Intel Adopts ‘Holistic’ Approach to AI

By George Leopold

A developers’ conference is generally regarded as an indication the host company is all-in on a particular technology. Intel Corp.’s inaugural AI DevCon highlights its strategy of moving beyond its dominant position in the server and other processor markets to focus on “the AI-driven future of computing.”

The two-day event in San Francisco focused on forging a “holistic” approach to developing enterprise-scale AI applications while bringing together data scientists, machine and deep learning specialists as well as application developers.

Naveen Rao, general manager of Intel’s Artificial Intelligence Products Group, said a company survey found that more than half of chip maker’s U.S. enterprise customers are using cloud-based tools running on its Xeon processors for “initial” AI workloads. Beyond Xeon CPUs, Intel also is expanding its AI portfolio to address diverse AI workloads running on its Nervana neural networking processor along with FPGAs.

(This week, Intel unveiled its Xeon 6138P processor that integrates its mainstream Xeon CPU server chip with its Arria FPGA.)

Rao stressed the performance of its line of Xeon Scalable Processors have optimized for machine learning model training and inference. The chip maker (NASDAQ: INTC) is betting the approach will entice customers to leverage their existing Intel CPU infrastructure to take “their first steps toward AI,” Rao said.

Intel also announced several AI initiatives this week with industry partners focused on deep neural networks for drug discovery and another on Internet of Things development. The latter project with C3 IoT seeks to develop an “AI appliance” based on Intel’s development hardware.

On the software side, Rao said Intel is integrating deep learning frameworks such as TensorFlow and MXNet—two popular deep learning frameworks developed by Google (NASDAQ: GOOGL) and Amazon (NASDAQ: AMZN), respectively—onto its nGraph universal deep neural network model compiler. The tool also supports ONNX, an open deep learning model standard spearheaded by Microsoft (NASDAQ: MSFT) and Facebook (NASDAQ: FB), which in turn enables nGraph to support PyTorch, Caffe2, and CNTK.

Meanwhile, company executives are championing a broad-brush approach to AI development, emphasizing the chip maker’s hefty investments in an expanding AI ecosystem. Intel CEO Brian Krzanich ticked off a list of investments in AI startups such as Data Robot and Lumiata. Intel Capital’s AI investment totals more than $1 billion, Krzanich said.

At the same time, the silicon leader is rolling out new scalable processors designed for AI workloads, including “purpose-built silicon” for deep learning training code-named “Lake Crest,” the Intel chief noted. “We are 100-percent committed to creating the roadmap of optimized products to support emerging mainstream AI workloads,” Krzanich declared.

Recent items:

Inside Intel’s nGraph, a Universal Deep Learning Compiler

Intel Details AI Hardware Strategy for Post-GPU Age

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