Timesdelhi.com

September 20, 2018
Category archive

Enterprise

AI could help push Neo4j graph database growth

in Artificial Intelligence/big data/Delhi/Developer/Enterprise/graph databases/India/machine learning/neo4j/open source/Politics by

Graph databases have always been useful to help find connections across a vast data set, and it turns out that capability is quite handy in artificial intelligence and machine learning too. Today, Neo4j, the makers of the open source and commercial graph database platform, announced the release of Neo4j 3.5, which has a number of new features aimed specifically at AI and machine learning.

Neo4j founder and CEO Emil Eifrem says he had recognized the connection between AI and machine learning and graph databases for awhile, but he says that it has taken some time for the market to catch up to the idea.

“There has been a lot momentum around AI and graphs…Graphs are very fundamental to AI. At the same time we were seeing some early use cases, but not really broad adoption, and that’s what we’re seeing right now,” he explained.

AI graph uses cases. Graphic: Neo4j

To help advance AI uses cases, today’s release includes a new full text search capability, which Eifrem says has been one of the most requested features. This is important because when you are making connections between entities, you have to be able to find all of the examples regardless of how it’s worded — for example, human versus humans versus people.

Part of that was building their own indexing engine to increase indexing speed, which becomes essential with ever more data to process. “Another really important piece of functionality is that we have improved our data ingestion very significantly. We have 5x end-to-end performance improvements when it comes to importing data. And this is really important for connected feature extraction, where obviously, you need a lot of data to be able to train the machine learning,” he said. That also means faster sorting of data too.

Other features in the new release include improvements to the company’s own Cypher database query language and better visualization of the graphs to give more visibility, which is useful for visualizing how machine learning algorithms work, which is known as AI explainability. They also announced support for the Go language and increased security.

Graph databases are growing increasingly important as we look to find connections between data. The most common use case is the knowledge graph, which is what lets us see connections in a huge data sets. Common examples include who we are connected to on a social network like Facebook, or if we bought one item, we might like similar items on an ecommerce site.

Other use cases include connected feature extraction, a common machine learning training techniques that can look at a lot of data and extract the connections, the context and the relationships for a particular piece of data, such as suspects in a criminal case and the people connected to them.

Neo4j has over 300 large enterprise customers including Adobe, Microsoft, Walmart, UBS and NASA. The company launched in 2007 and has raised $80 million. The last round was $36 million in November 2016.

News Source = techcrunch.com

GitLab raises $100M

in bitbucket/computing/Delhi/Developer/Electric Cloud/Enterprise/funding/Fundings & Exits/Git/GitHub/gitlab/ICONIQ/India/New Relic/Politics/software engineering/version control by

GitLab, the developer service that aims to offer a full lifecycle DevOps platform, today announced that it has raised a $100 million Series D funding round at a valuation of $1.1 billion. The round was led by Iconiq.

As GitLab CEO Sid Sijbrandij told me, this round, which brings the company’s total funding to $145.5 million, will help it enable its goal of reaching an IPO by November 2020.

According to Sijbrandij, GitLab’s original plan was to raise a new funding round at a valuation over $1 billion early next year. But since Iconiq came along with an offer that pretty much matched what the company set out to achieve in a few months anyway, the team decided to go ahead and raise the round now. Unsurprisingly, Microsoft’s acquisition of GitHub earlier this year helped to accelerate those plans, too.

“We weren’t planning on fundraising actually. I did block off some time in my calendar next year, starting from February 25th to do the next fundraise,” Sijbrandij said. “Our plan is to IPO in November of 2020 and we anticipated one more fundraise. I think in the current climate, where the macroeconomics are really good and GitHub got acquired, people are seeing that there’s one independent company, one startup left basically in this space. And we saw an opportunity to become best in class in a lot of categories.”

As Sijbrandij stressed, while most people still look at GitLab as a GitHub and Bitbucket competitor (and given the similarity in their names, who wouldn’t?), GitLab’s wants to be far more than that. It now offers products in nine categories and also sees itself as competing with the likes of VersionOne, Jira, Jenkins, Artifactory, Electric Cloud, Puppet, New Relic, and BlackDuck.

“The biggest misunderstanding we’re seeing is that GitLab is an alternative to GitHub and we’ve grown beyond that,” he said. “We are now in nine categories all the way from planning to monitoring.”

Sijbrandij notes that there’s a billion-dollar player in every space that GitLab competes it. “But we want to be better,” he said. “And that’s only possible because we are open core, so people co-create these products with us. That being said, there’s still a lot of work on our side, helping to get those contributions over the finish line, making sure performance and quality stay up, establish a consistent user interface. These are things that typically don’t come from the wider community and with this fundraise of $100 million, we will be able to make sure we can sustain that effort in all the different product categories.”

Given this focus, GitLab will invest most of the funding in its engineering efforts to build out its existing products but also to launch new ones. The company plans to launch new features like tracing and log aggregation, for example.

With this very public commitment to an IPO, GitLab is also signaling that it plans to stay independent. That’s very much Sijbrandij’s plan, at least, though he admitted that “there’s always a price” if somebody came along and wanted to acquire the company. He did note that he likes the transparency that comes with being a public company.

“We always managed to be more bullish about the company than the rest of the world,” he said. “But the rest of the world is starting to catch up. This fundraise is a statement that we now have the money to become a public company where we’re not we’re not interested in being acquired. That is what we’re setting out to do.”

News Source = techcrunch.com

Einstein Voice gives Salesforce users gift of gab

in Artificial Intelligence/Cloud/Delhi/Einstein/Enterprise/India/natural language processing/Politics/Salesforce/voice assistants/voice recognition by

Salespeople usually spend their days talking. They are on the phone and in meetings, but when it comes to updating Salesforce, they are back at the keyboard again typing notes and milestones, or searching for metrics about their performance. Today, Salesforce decided to change that by introducing Einstein Voice, a bit of AI magic that allows salespeople to talk to the program instead of typing.

In a world where Amazon Alexa and Siri make talking to our devices more commonplace in our non-work lives, it makes sense that companies are trying to bring that same kind of interaction to work.

In this case, you can conversationally enter information about a meeting, get daily briefings about key information on your day’s meetings (particularly nice for salespeople who spend their day in the car) and interact with Salesforce data dashboards by asking questions instead of typing queries.

All of these tools are designed to make life easier for busy salespeople. Most hate doing the administrative part of their jobs because if they are entering information, even if it will benefit them having a record in the long run, they are not doing their primary job, which is selling stuff.

For the meetings notes part, instead of typing on a smartphone, which can be a challenge anyway, you simply touch Meeting Debrief in the Einstein Voice mobile tool and start talking to enter your notes. The tool interprets what you’re saying. As with most transcription services, this is probably not perfect and will require some correcting, but should get you most of the way there.

It can also pick out key data like dates and deal amounts and let you set action items to follow up on.

Gif: Salesforce

Brent Leary, who is the founder and principal analyst at CRM Essentials says this is a natural progression for Salesforce as people get more comfortable using voice interfaces. “I think this will make voice-first devices and assistants as important pieces to the CRM puzzle from both a customer experience and an employee productivity perspective,” he told TechCrunch.

It’s worth pointing out that Tact.AI has been doing this for some time on top of Salesforce giving this type of voice interaction for Salesforce users. It’s likely ahead of Salesforce at this point, but Leary believes having Salesforce enter the voice arena will probably benefit the startup more than hurt it.

“The Salesforce tide will lift all boats, and companies like Tact will see their profile increased significantly because while Salesforce is the leader in the category, it’s share of the market is still less than 20% of the market,” he pointed out.

Einstein is Salesforce’s catch-all brand for its artificial intelligence layer. In this case it’s using natural language processing, voice recognition technology and other artificial intelligence pieces to interpret the person’s voice and transcribe what they are saying or understand their request better.

Typically, Salesforce starts with a small set of functionality and the builds on that over time. That’s very likely what they are doing here, coming out with a product announcement in time for Dreamforce, their massive customer conference next week,

News Source = techcrunch.com

Fresh out of Y Combinator, Leena AI scores $2M seed round

in Artificial Intelligence/chatbots/Delhi/Enterprise/funding/hr/India/Leena AI/natural language processing/Politics/Startups/TC/Y Combinator by

Leena AI, a recent Y Combinator graduate focusing on HR chatbots to help employees answer questions like how much vacation time they have left, announced a $2 million seed round today from a variety of investors.

Company co-founder and CEO Adit Jain says the seed money is about scaling the company and gaining customers. They hope to have 50 enterprise customers within the next 12-18 months. They currently have 16.

We wrote about the company in June when it was part of the Y Combinator Summer 2018 class. At the time Jain explained that they began in 2015 in India as a company called Chatteron. The original idea was to help others build chatbots, but like many startups, they realized there was a need not being addressed, in this case around HR, and they started Leena AI last year to focus specifically on that.

As they delved deeper into the HR problem, they found most employees had trouble getting answers to basic questions like how much vacation time they had or how to get a new baby on their health insurance. This forced a call to a help desk when the information was available online, but not always easy to find.

Jain pointed out that most HR policies are defined in policy documents, but employees don’t always know where they are. They felt a chatbot would be a good way to solve this problem and save a lot of time searching or calling for answers that should be easily found. What’s more, they learned that the vast majority of questions are fairly common and therefore easier for a system to learn.

Employees can access the Leena chatbot in Slack, Workplace by Facebook, Outlook, Skype for Business, Microsoft Teams and Cisco Spark. They also offer Web and mobile access to their service independent of these other tools.

Photo: Leena AI

What’s more, since most companies use a common set of backend HR systems like those from Oracle, SAP and NetSuite (also owned by Oracle), they have been able to build a set of standard integrators that are available out of the box with their solution.

The customer provides Leena with a handbook or a set of policy documents and they put their machine learning to work on that. Jain says, armed with this information, they can convert these documents into a structured set of questions and answers and feed that to the chatbot. They apply Natural Language Processing (NLP) to understand the question being asked and provide the correct answer.

They see room to move beyond HR and expand into other departments such as sales or customer service that could also take advantage of bots to answer a set of common questions. For now, as a recent YC graduate, they have their first bit of significant funding and they will concentrate on building HR chatbots and see where that takes them.

News Source = techcrunch.com

Google’s Work Insights helps businesses better understand how they work

in Delhi/Enterprise/G Suite/Google/India/Politics/work by

At an event in Tokyo, Google today announced the launch of Work Insights, a new tool that gives businesses more insights into how their employees use the company’s G Suite productivity tools and how teams collaborate using those tools.

In addition, Google is also launching its investigation tool for helping business better secure their data in G Suite into general availability.

“Work Insights is a tool built specifically to help businesses measure and understand the impact of digital transformation within their organizations, driven by G Suite,” Reena Nadkarni, a group product manager for G Suite, explains in today’s announcement. Data is aggregated at the team level (where a team needs to have 10 people or more) to help businesses understand how their employees are adapting G Suite apps.

As enterprises bet on one vendor or the other, there’s always a bit of a transition period and not everybody makes the move quite as quickly as others. Most of these tools, though, only really work when the whole company adopts them. That’s especially true for communication tools like Slack, Hangouts Chat/Meet or Microsoft Teams, but also for productivity tools like G Suite.

The other use cases here, though, is actually far more interesting. Work Insights will also give companies a view of how users on different teams interact with each other (think the marketing and sales teams). If they are working on documents together, then they are probably working well together, too (or just leaving acerbic comments on marketing presentations, but you get the general idea here).

“This insight can help executives identify opportunities to strengthen collaboration and reduce siloes,” Nadkarni writes. Since few executives ever say that they want less collaboration and more siloes, chances are we’ll see quite a few companies adopt these tools.

 

News Source = techcrunch.com

1 2 3 65
Go to Top