Well, it looks like HubSpot co-founder and CTO Dharmesh Shah accidentally leaked the chatbot he's been working on for the company -- something he teased on Medium a few weeks ago. It's called GrowthBot, and its website calls it a "chatbot for marketing and sales." The bot is active on Facebook Messenger and through text message, and it lets you perform a number of queries, including "find companies in Boston using HubSpot," "what tech does Drift.com It also has a list of HubSpot-specific commands, showing that it may already integrate with some of HubSpot's software: The bot has commands for Google Analytics ("how is traffic this week?") and Medium ("start medium post"). Shah confirmed to BostInno that he accidentally tweeted a link to GrowthBot's site -- which is where we saw it -- in what was intended to be a private conversation.

The next BriefingsDirect business innovation thought leadership discussion focuses on how new modes of buying and evaluating goods and services are disrupting business procurement. We'll hear now from a leading industry analyst on how machine learning, cloud services, and artificial intelligence-enabled human agents are all combining to change the way that companies can order services, buy goods, and even hire employees and contractors. This business process innovation exchange comes to you in conjunction with the Tradeshift Innovation Day held in New York on June 22, 2016. To learn more about how new trends are driving innovation into invoicing and spend management, please join me in welcoming Pierre Mitchell, Chief Research Officer and Managing Director at Azul Partners, where he leads the Spend Matters Procurement research activities. The discussion is moderated by me, Dana Gardner, Principal Analyst at Interarbor Solutions.

KisanHub, a Cambridge, UK-based agtech startup, raised over 1m in funding. The round was led by Notion Capital with participation from NIAB, an international center for plant research, crop evaluation and agronomy. The company intends to use the funds for R&D, sales and customer delivery. Led by Dr Sachin Shende, CEO, Giles Barker, COO, KisanHub provides a SaaS based farming enterprise software platform which leverages precision agriculture, big data, cloud computing, machine learning and mobile to deliver decision points to over one thousand farmers and multiple large enterprises. The company also has operations in Pune.

I just got a new laptop with a GTX 960 graphics card and I decided to jump on the DNN bandwagon, but just going to Nvidia's page it enumerates more than 10 libraries, some more and some less known. For reference, my background is Python/R and Bayesian ML.

I'm new to machine learning and been learning SciKit Learn and really love it. It is amazingly easy and allows really quick results for someone with no experience. My friend says it is all deep learning and neural networks. How hard is the transition to tensorflow, theano and less if I only know SciKit Learn and about 6-7 algorithms. I understand kfolds, CV and gridsearch. Outside of the simplicity and speed is there any reason to continue learning SciKit Learn and how much will carry over to neural networks and deep learning?

Facebook's recent chatbot announcement about delivering ecommerce to the service's extensive user base has put artificial intelligence into the spotlight again. For years, software design has traditionally consisted of three fields, but there may soon be a fourth. Joining UX, UI, and graphic and interaction design is an idea known as "consciousness design" that will emerge as A.I. assistants grow in popularity. Amazon Echo and other A.I. assistants are among the pioneers of virtually "interface-less" experiences that make consciousness design central to product success. The idea is not so much to offer a simple search that delivers less-than-desired results, which is what Facebook bots basically do, but rather to offer a real customized experience that harnesses artificial intelligence to power the coming revolution.

Most of the technologies being developed will help reduce large numbers of traffic accidents, deaths and serious injuries.

Big data in healthcare can now be measured in exabytes, and every day more data is being thrown into the mix in the form of patient-generated information, wearables and EHR systems. Traditional methods of analysis are no longer enough to handle, let alone take proper advantage of, the potential that healthcare data holds. This is where deep machine learning (or simply, "deep learning") comes in. However, its greatest power lies in its ability to extract value from data in ways that humans and traditional machine learning methods cannot. Deep machine learning has applications in a number of healthcare areas.

What does the future of big data hold? NTT Data released the 4 areas of information technology trends and 8 technology trends in its report "Looking Ahead: Technology Trends Driving Business Innovation." NTT Data divides the impact of big data into information society trends and technology trends. Information society trends include all things related to the individual and their devices. The growing influence of individuals will transform existing societies and industries.

In this episode of the O'Reilly Data Show, I spoke with Yishay Carmiel, president of Spoken Labs. As voice becomes a common user interface, the need for accurate and intelligent speech technologies has grown. And although computer vision is a common entry point for deep learning, some of the most interesting commercial applications of deep neural networks are in speech recognition. Carmiel has spent several years building commercial speech applications, and along the way he has witnessed (and helped architect) massive improvements in speech technologies.