{"id":9541,"date":"2017-10-10T15:27:28","date_gmt":"2017-10-10T15:27:28","guid":{"rendered":"https:\/\/rsoftsolution.com\/blog\/petuum-secures-93m-series-b-to-push-ai-into-the-mainstream.html"},"modified":"2017-10-10T15:27:28","modified_gmt":"2017-10-10T15:27:28","slug":"petuum-secures-93m-series-b-to-push-ai-into-the-mainstream","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/petuum-secures-93m-series-b-to-push-ai-into-the-mainstream.html","title":{"rendered":"Petuum secures $93M Series B to push AI into the mainstream"},"content":{"rendered":"


\n<\/p>\n

With a shortage of machine learning developers bearing down on the industry, startups and big tech companies alike are moving to democratize the tools necessary to commercialize artificial intelligence. The latest startup,\u00a0Petuum<\/a>, is announcing a $93 million Series B this morning from Softbank<\/a> and\u00a0Advantech Capital<\/a>.<\/p>\n

Founded last year by\u00a0Dr. Eric Xing, a\u00a0Carnegie Mellon machine learning professor, Dr.\u00a0Qirong Ho and Dr. Ning Li,\u00a0Petuum is building software to facilitate two components of machine learning development. First, the team is automating aspects of data preparation and machine learning model selection. This is useful for novices that might otherwise struggle to even make use of common machine learning frameworks like TensorFlow and Caffe.<\/p>\n

Once models have been selected,\u00a0Petuum can also assist developers in optimizing for specific hardware constraints. This means\u00a0virtualizing hardware to remove barriers \u2014 taking out the extra step of managing a distributed GPU cluster.<\/p>\n

\u201cThe way we treat AI is not as an artisanal craft,\u201d Dr.\u00a0Xing explained to me in an interview. \u201cWe are trying to create very standardized building blocks that can be assembled and reassembled like legos.\u201d<\/p>\n

\"\"<\/a><\/p>\n

Petuum founder Dr. Eric Xing inside the startup\u2019s offices in\u00a0Pittsburgh<\/p>\n

The point here isn\u2019t to solve every problem in machine learning, but rather to automate enough of the process that industry can move from 0 to 1. That said,\u00a0Petuum is attempting to build for both the expert and the novice \u2014 a tough balance to strike.<\/p>\n

\u201cEveryone knows how to use Excel,\u201d asserted\u00a0Dr.\u00a0Xing. \u201cA layman can use Excel to create a table.\u00a0A highly skilled statistician modeling certain phenomenons can still use Excel.\u201d<\/p>\n

The other challenge facing\u00a0Petuum is one of market strategy. As the tech industry grapples with its dumb money in AI problem, many investors have turned to heuristics to manage uncertainty \u2014 most popular of which is that horizontal platform AI plays don\u2019t work.<\/p>\n

The concern is that it\u2019s difficult to outgun Google and Amazon in the machine learning-as-a-service space as a startup that needs to balance feature development and spending.\u00a0Dr.\u00a0Xing deferred to the skill of his team and while he didn\u2019t directly mention it \u2014 the goldmine from Softbank won\u2019t hurt. This is something that others like H2O.ai<\/a> and\u00a0Algorithmia<\/a> can\u2019t claim to date.<\/p>\n

To the company\u2019s credit, it is starting by going after healthcare and fintech customers. Though\u00a0in the long run, Petuum doesn\u2019t intend to cover every vertical.\u00a0Petuum is working with beta testers in different industries so that in the future,\u00a0outsiders can develop and deploy\u00a0solutions on top of the platform.<\/p>\n

Today\u2019s investment comes from Softbank proper rather than the $93 billion Softbank\u00a0Vision Fund<\/a>. It\u2019s unclear whether Softbank intends to shift the investment into the fund in the future.\u00a0Petuum currently claims 70 employees and says that it will be expanding simultaneously in\u00a0product, sales and marketing.<\/p>\n

<\/p>\n

Featured Image: Petuum<\/small><\/p>\n

Article source: http:\/\/feedproxy.google.com\/~r\/techcrunchIt\/~3\/fmbYIFfinsU\/<\/p>","protected":false},"excerpt":{"rendered":"

With a shortage of machine learning developers bearing down on the industry, startups and big tech companies alike are moving to democratize the tools necessary to commercialize artificial intelligence. The <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[19],"tags":[25],"class_list":["post-9541","post","type-post","status-publish","format-standard","hentry","category-enterprise-software","tag-enterprise"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t