Global Enterprise Data Cloud Storage Software Market 2020 Trends Analysis and (COVID-19) Effect Analysis | Key Players Market With COVID-19 Impact Analysis | In Depth Insight | Growth & Research Finding TO 2025 TechnoWeekly
“nigeria startups when:7d” – Google News
The world of distributed computing took on a new profile this year when Folding@home, a 20-year-old distributed computing project, found itself picking up thousands of new volunteers to help COVID-19 researchers generate more computing power to fold proteins and run other calculations needed for screening potential drug compounds to fight the novel coronavirus. Today, a startup that is also tapping the potential and opportunity in distributed computing is announcing a round of growth funding to continue its own work.
Anyscale, a startup founded by a team out of UC Berkeley that created the Ray open-source Python framework for running distributed computing projects, has raised $ 40 million.
It plans to use the capital to continue developing Anyscale, a platform built on Ray that will make Ray usable not just by high-level developers and computing specialists, but any technical people who are looking to run projects that require large amounts of computing power.
Ion Stoica, Anyscale’s executive chairman who co-founded the company with Robert Nishihara, Philipp Moritz and Berkeley professor Michael I. Jordan, said in an interview that the company is tapping into a moment spurred not just by the events of 2020 but by the bigger demand from companies — spurred by the growth of cloud computing, major digital transformation of their systems and a need to go that extra mile to remain competitive. Organizations are becoming more ambitious in their technology strategies and goals, whether they are tech companies or not.
“At a high level, the trend that we see is that all applications are distributed and running on clusters, but building these applications is incredibly hard and requires teams with the right expertise,” said Stoica. “What we are trying to build will make it as easy to build a distributed computing project as it would be to run a program on your laptop. It will mean ordinary developers will be able to build scalable applications just like Google can build today.”
The company’s first build of Anyscale — which will let organizations build multi-cloud applications from a single machine and use serverless architecture that scales up and down to meet application demands — has yet to launch commercially: it is in a private beta and the plan is to launch it fully next year.
There has been interest from financial services, retail and manufacturing companies, Stoica said, with companies working in design, informatics and medical research (and COVID-19 vaccines) also using the private beta.
The Series B is being led by previous investor NEA, with Andreessen Horowitz (a16z), Intel Capital and Foundation Capital also participating. A16z led the company’s Series A less than a year ago (a $ 20 million round in December).
Intel, meanwhile, is a strategic investor. Along with other tech giants like Microsoft, Intel is using Ray’s distributed computing model to run projects.
Stoica — who also co-founded Databricks, Conviva and was one of the original developers of Apache Spark — and Nishihara declined to comment in an interview on Anyscale’s valuation, but Stoica confirmed that the round was oversubscribed. The company has now raised just over $ 60 million.
While the startup continues to build out Anyscale, in the last year it has also been making more headway with Ray, which they also maintain.
At the Ray Summit — Anyscale’s conference for developers run as a virtual event at the end of September — Anyscale released Ray 1.0, which provides, in addition to a universal serverless compute API, an expanded library to use on Ray 1.0. Nishihara described it as a “huge milestone,” not least because it is one step along the path for the bigger vision they have for Anyscale to be used by non-tech companies for tech work.
A typical example was a recent recommendation algorithm built by Intel for Burger King. “The thing that is hard to do is not making the recommendations but learning from the interactions that users are having, and the choices they are making, and having that experience reflected back very rapidly,” he said. It’s a process that can be done in other ways, but with a far less good user experience due to lags.
This past year Nishihara said that interest in Ray has seen “tremendous growth,” but that it’s hard to say whether that is because of people working from home or just wider computing trends.
“It’s clear if anything that the pandemic is accelerating the transition,” said Stoica. “Ray has good support for the cloud, including Azure, Google Cloud Platform and others, which makes it quite compelling.”
We’ve seen an interesting trend in enterprise IT, where startups are finding an opportunity in the market by making it possible for non-technical organizations to bridge the digital divide, by providing better access to the most technical advances in computing to organizations beyond those that can build and operate such tools themselves. Just as groups like Element AI are working on ways to democratize advances in AI, the same kind of tech built, acquired and used by the likes of Apple, Google and Amazon, so too is Anyscale looking to do the same in enterprise computing.
And the two areas of AI and computing, of course, are interconnected: these days you need vast amounts of computing power to run AI applications, something the average company typically lacks.
“The demand for distributed computing continues to increase with the widespread adoption of AI and machine learning in application development,” said Pete Sonsini, general partner at NEA, in a statement. “Still, scaling applications on clusters remains extremely challenging. Serverless computing is emerging as the preferred platform for developing distributed applications. Unfortunately, today’s serverless offerings support only a limited set of applications, and most of them are cloud-specific—but not Ray and Anyscale. The company’s path thus far bears the hallmarks of a standout technology pioneer, and we’re thrilled to partner with the team through this next phase bridging their open source and commercial offerings.”
Even given how much attention 2020 has brought to no-code startups and their low-code relatives, the investment stood out as outsized — and rapid. Previously, Unqork added $ 51 million to its Series B earlier this year, bringing that round to a total of around $ 131 million.
To see the company raise even more this quickly signaled that something was afoot.
So we sent in a raft of questions to the company to better understand the demand that it is seeing in the market for its service. I want to better understand not only how Unqork managed to attract such a massive new check, but also what its notes tell us about the market for no-code services that help business build apps, a key portion of the no-code/low-code market.
What might be working for Unqork, in other words, could be working for other players in the space. And, if so, the whole no-code/low-code world could be enjoying an even sharper tailwind than we previously anticipated.
We’ll also bring in a few notes from Laela Sturdy, a general partner at Alphabet’s Capital G investing group. She led the company’s Series B and sits on its board. Luckily, we have a grip of her thoughts from our August no-code/low-code investor survey. Let’s get into it!
Briefly, the round. Unqork raised $ 207 million at a roughly $ 2 billion price point — post-money, we presume — in a Series C led by BlackRock. Other money buckets took part, including funds from Hewlett Packard Enterprise, Schonfeld Strategic Advisors, Sunley House Capital Management, Eldridge and Fin Venture Capital, per the company. Prior investors, including the aforementioned Capital G, along with Broadridge Financial Solutions, Aquiline Technology Growth, Goldman Sachs and World Innovation Lab also took part.
That is a long list of names. But it takes a while to add up to nine figures of capital, so perhaps the party-round style Series C is not too surprising.
Regardless, the firm is now incredibly well-capitalized and we can move onto more interesting things. Namely, how the company managed to raise so very much money. The Exchange asked Unqork a few questions:
- First, what is driving the demand for more business apps, a topic we’ve explored before.
- Second, we wanted to know what impact COVID-19 has had on the business; has the pandemic provided a dramatic lift to Unqork’s business, and, if so, did that drive its growth forward and help it secure the Series C?
- And, finally, we asked about the company’s sales cadence; is Unqork seeing faster sales cycles? If so, it could indicate that the market is moving toward no-code business app creation, lowering the hurdles that startups working in the space have to clear to snag new customers.
I am running a startup and I often find my team often asks me questions that I have no answer too. Although we discussed on the topics earlier. I feel that we loose valuable data over time and we have no way to store it.
So, what if we build a system where all meeting details will be captured and then we can go through at any point of time and then build our own organisational Google.
As, I am already running a text-analytics company I thought it can be done easily. So, here goes my wild imagination.
- Create a BOT that will join all the meeting platforms and record the meetings.
- Store the meeting data and retrive information, use NLP and AI to categorise the data.
So do this, we have build the first version of the product –
- An AI-BOT that joins all the meetings on Google Meet, Zoom, Microsoft Teams.
- Action Items + Summary + Highlights + Decision Points + Questions + Metrics
- Full-Transcript + Speaker information.
- Meeting notes share functionality with others.
This also servers as a personal NOTE taker. And I personally feel with this, we can save 30% of our daily work time.
Eventually we can use this data as a Google for enterprises, do data will be lost and you can always refer back to all your information. In the future, we can build a search engine for your enterprise.
If want to check out the first version of the application here is the link – www.rechord.ai
We are in BETA, so if please excuse us if you will encounter any problem.
Since 2011, European startup studio eFounders has launched 27 companies with a focus on software-as-a-service companies trying to improve the way we work. Some of them have been quite successful, such as Front and Aircall.
And the company is working on its next batch of startups. “We're particularly inspired by the new wave of productivity tools, that is ever more collaborative and flexible,” eFounders co-founder Thibaud Elziere said in a statement
In exchange for financial and human resources, eFounders keeps a significant stake in its startups. Ideally, startups raise a seed round and take off on their own after a year or two.
Here’s what’s coming up from eFounders.
Canyon is a product for legal teams that want to ditch Word, PDF documents and emails. It starts with a central hub to hold all your drafts and documents. This way, you can track progress, get the latest document version and see the context around a document. Given that it is tailored for legal teams, it should work a bit better than a shared Dropbox folder.
You can create templates to reuse them later, see related emails directly in Canyon’s interface and invite other people so that they can have a look at what you’ve been working on.
Kairn is a task manager that tries to get out of the way as much as possible. When you’re working on your computer, you can add tasks directly from the app that you’re already using.
For instance, you can imagine adding a task by starring an email conversation in Gmail, forwarding a message to a WhatsApp bot or starring a message in Slack. There’s also a quick add window that you can trigger with a keyboard shortcut.
Read my full article on Kairn:
Crew is focused on new hires and job applications. Given that many companies are actively looking for interesting candidates, Crew isn’t just a way to passively collect applications.
It lets you create automated workflows and handle everything you’d expect from a recruitment platform.
Collective is a product for freelancers who want to work together and form groups. It should make it easier to send a contract to a client that involves multiple freelancers working on the contract. Collective will make it easier to remain legally compliant.