Atlassian has developed a new search tool  —  Atlassian  Rovo — that can surface data from a variety of third-party apps. Rovo, currently in preview, provides a chatbot interface to help workers access information across their organization,and even decipher workplace jargon. 

“Atlassian Rovo is designed to unlock knowledge discovery and accelerate action across the organization,” said Jamil Valliani, head of product AI at Atlassian. “Think of Rovo as a large knowledge model for your company that allows team members to move and act faster.”

There are three key elements to Rovo: Search, Chat, and Agents. 

Rovo Search expands on existing search functions in Atlassian apps, with the ability to access documents from a range of external sources in addition to data held in tools such as Jira and Confluence. This means surfacing information in third-party productivity tools such as Slack, Microsoft Teams, Figma and GitHub, as well as file storage platforms such as Google Drive and Microsoft SharePoint.  

Atlassian also plans to let Rovo access data from in-house applications, including finance or HR apps.

One way to access Rovo search is via the search bar in various Atlassian apps. A list of search results containing related documents is presented, as well as more detailed “knowledge cards” that present information relating to a project, for instance, or a team. Here, the knowledge card might contain links to related files, as well as information on project status, listed contributors, and more.  

Rovo Search can also learn and explain unfamiliar jargon specific to an industry or individual business based on the organization’s documents. This enables Rovo to provide definitions for acronyms and terms that appear within a Confluence document, for exam-le. It’s proved to be a popular feature, Atlassian said, and is used by three-quarters of staff testing Rovo. 

A semantic search function helps teams “connect with what they are looking for,” said Julie Mohr, principal analyst at Forrester, as well as “knowledge they didn’t know existed.” This helps employees “work the way they want to work with a comprehensive set of expressive tools — from video to pages, structured and unstructured, it is all knowledge,” she said. 

Another way to search for information is via Rovo Chat. Similar to the conversational interfaces in Microsoft’s Copilot, OpenAI’s ChatGPT, and others, the chatbot responds to user questions in natural language, with answers based on data held in documents across an organization. Links are provided to the original source.

Atlassian

Another aspect of Rovo that relies on generative AI is the addition of workflow automation “agents.” Accessible via the Rovo Chat sidebar, the Rovo Agents are tailored to a specific task. For instance, Rovo Agents can be designed to generate and review marketing content, collate feedback from various sources, or streamline processes such as clearing up Jira backlogs and organizing Confluence pages. 

Users can create their own Rovo Agents using a no-code text interface or Atlassian’s Forge app development platform. Atlassian expects there will be around 20 pre-built agents available when Rovo launches. 

Canva’s design software is an example of an Atlassian partner building its own agent. “There’s going to be a Canva agent that helps with generating simple artwork for social media posts, things that you don’t need an expert designer to do,” said Valliani. 

Atlassian

“Generative AI  has so much potential in knowledge management,” said Mohr. “Atlassian is taking the power of Confluence and improving those capabilities with sound knowledge management practices combined, with new features that take advantage of genAI.”

Making it easier to access information across an organization also means there’s potential for users to access sensitive documents. Atlassian said Rovo will respect permissions around the content it has access to, with restricted data in third-party apps remaining private.

As with any API or integration, businesses should assess risks when connecting to external systems and ensure that adequate permissions are in place around documents, said Mohr. But those risks shouldn’t put businesses off from widening access to information held across their organization, she said.

“[T]hink of all the undiscovered knowledge, all the ideas that are locked up in folders and private stores,” said Mohr. “There is a cultural change that needs to take place, where people as well as the systems understand the value of free access to knowledge.” 

Opening employee access to a wider range of information can “empower more collaboration and learning,” said Mohr, with businesses able to restrict access “when it is genuinely needed for regulatory or compliance purposes.”

Atlassian customers can join a waitlist to access Rovo in beta. The general availability date hasn’t yet been announced. 

Rovo will be sold as an add-on alongside cloud editions of Atlassian products, with a flexible pricing model based on unique users. More details will be announced at the general availability launch.

Amazon Web Services (AWS) on Tuesday said its generative AI-based assistant for business applications — Amazon Q Business — is now generally available.

Introduced at re:Invent last year, Amazon Q Business can be used to have conversations, solve problems, generate content, gain insights, and take action by connecting to a company’s information repositories, data, and enterprise systems, AWS  said. 

To use Q as an assistant for business apps, enterprises first need to configure the generative AI (genAI) assistant by connecting it to existing data sources, which can include AWS’ S3 storage service as well as applications from vendors including Salesforce, Microsoft, Google, and Slack. 

Q currently supports connectors for more than 40 tools and applications.

Additionally, AWS has added a new app-building capability to Amazon Q Business, which is a web-based application.

Named Amazon Q Apps and currently in preview, the feature will allow enterprise users, including business users, to develop applications based on their enterprise data using natural language.

“With Q Apps, employees simply describe the app they want, in natural language, or they can take an existing conversation where Amazon Q Business helped them solve a problem, and with one click, Q will instantly generate an app that accomplishes their desired task that can be easily shared across their enterprise,” said Mai-Lan Tomsen Bukovec, vice president of technology at AWS. 

Q Apps could include HR or marketing apps designed either to onboard employees or to automate tasks. They can be accessed via the Amazon Q Business application environment, the company said; Q Apps is enabled by default and can be switched off from the Amazon Q Business console.

Bukovec said a Q App is made up of a collection of cards, with each card serving as a  user interface element that can be combined with other cards to generate an application.

“Cards take in user input, support file uploads, connect to other cards, generate text output, and allow actions through Amazon Q Business plugins,” the company said in a blog post. 

Enterprise users can add to the Q app, edit it, or delete a card, AWS said. 

At a more basic level, text output and plugin cards contain prompt instructions that determine how Amazon Q Business is queried to generate a response. 

“When enterprise users use the Amazon Q Apps Creator, relevant cards are automatically generated with prefilled prompts. Users can further refine these prompts using simple, natural language,” the company said.

“When writing or editing a prompt for a card, your users can reference other cards using ‘@’ mention to select from the list of cards in the app. Users can also instruct in the prompt to reference your enterprise data already in Amazon Q Business,” AWS said.

Amazon Q Apps developed by one enterprise user can be shared with other users across the company via the Amazon Q Apps library.

Q Apps can also be copied and customized by other users to create a new version. 

Amazon Q Business is available in two subscription models — Lite and Pro — which are priced at $3 and $20 per user, per month, respectively. The Pro subscription offers Amazon Q Apps, extended capabilities via custom plugins, and the ability to gain insights via Q in QuickSight. These capabilities are not available in the Lite subscription pack.

Additionally, the Pro subscription allows enterprise users to receive responses in a conversational interface up to approximately seven pages compared to the Lite pack’s limit of one page.

More than a year and a half after the CHIPS and Science Act was signed into law, the Biden Administration has begun divvying up $52.7 billion in funding and tax incentives meant to spur semiconductor production on US soil, though the actual funding has yet to be dispersed.

Over the past several months, the administration, which championed the legislation, has allocated about $29 billion in funding among chipmakers, including Samsung, TSMC and Intel. In return, various chip designers and makers have pledged about $300 billion in current and future projects in the US, according to the White House.

The most recent announcement last week was for $6.14 billion toward Micron’s plans to build new fabrication plants in upstate New York and perform upgrades elsewhere. To date, Intel has reaped the most in promised funds: $8.5 billion.

The Department of Commerce, which is administering the CHIPS Act, has spent months negotiating with semiconductor designers and fabricators to gain commitments from the companies and to achieve specific milestones in their projects before getting government payouts.

For example, negotiations between the federal government and TSMC resulted in the Taiwanese semiconductor designer and manufacturer being promised $6.6 billion in CHIPS Act funding; in return, the company bringing its most advanced 2nm process technology to US shores and adding plans for a third fabrication plant to its Arizona site.

At the beginning of 2023, TSMC, the world’s largest chip maker, began construction on its second chip fabrication plant near Phoenix, AZ. For Biden, TSMC’s three plants represented the flagship of the CHIPS Act incentive program. The TSMC project, however, stalled, and the company announced it had pushed back its completion date to 2025 due to problems finding skilled labor.

TSMC had promised to make a $40 billion investment in its US chip production plant. The investment represents the largest ever foreign investment in Arizona and one of the largest in US history.

Micron said it might spend up to $100 billion over the next 20 years to expand its US facilities, including a $15 billion memory chip plant in its home base of Boise, ID.

Industry analysts say the CHIPS Act is having its desired effect — the largest semiconductor designers and makers are investing in the US. By 2030, research firm IDC expects that 30% of the leading edge chip techology will be produced in the US, Western Europe, and Japan.

“Today, the semiconductor supply chain is concentrated in Asia,” said Mario Morales, a group vice president at IDC. “In fact, 100% of the global leading-edge chip capacity — 5nm and below — is only available in Taiwan and Korea. This will change dramatically by the end of the decade as leading-edge manufacturing is reestablished in the western hemisphere and in Japan.”

The latest round of CHIPS Act funding will support Micron’s construction of the first two fabs of a planned four-building “megafab” focused on leading-edge DRAM chip production. Each fab will have 600,000 square feet of cleanrooms, totaling 2.4 million square feet across the four facilities — the largest amount of cleanroom space ever announced in the US and the size of nearly 40 football fields.

The CHIPS Act’s purpose was to strengthen American supply chain resilience after the pandemic and counter China’s rising share of the market. The US share of global semiconductor fabrication capacity has fallen from about 36% in 1990 to about 10% in 2020, according to a Congressional Research Service report. Meanwhile, China’s share of chip manufacturing has grown nearly 50% over the past two years and now comprises about 18% of the world’s supply.

More CHIPS Acts to come?

The White House has argued that CHIPS Act spending will grow America’s share of the world’s leading-edge chip market to 20% by 2030. But experts say more government incentives will be needed to sustain and continue that growth domestically.

“The first CHIPS Act is just the start, there will be more funds needed to sustain and include other parts of the supply chain like materials, OSAT, design, and tools,” Morales said. “I expect that a second CHIPS Act will likely be higher in value than the first and will be approved sometime in the second half of this decade — in 2026 or 2027.”

Gaurav Gupta, a vice president analyst at Gartner Research, agreed with Morales that more funding is needed, and that while the current funding closes the capital cost gap, it does not do much for future operational costs. “Various factors will continue to make it expensive for fabs to be competitive here, like the regulatory and compliance framework that causes delays, labor compensation, higher utility rates, etc,” he said.

“So, if the US government really wants the needle to move and make this current CHIPS Act have a real impact, I expect version 2.0, 3.0 and onwards to come. When and what amounts they would be is hard to predict for now,” Morales said.

The current CHIPS Act includes $39 billion in subsidies for chip manufacturing on US soil along with 25% investment tax credits for costs of manufacturing equipment, and $13 billion for semiconductor research and workforce training.

In December, Computerworld contacted the Department of Commerce to discover why funds from the CHIPs Act had yet to be distributed. The Department said at the time it was still in “complex negotiations” with chip manufacturers to ensure the money is wisely spent.

In February, the Administration announced $1.5 billion for GlobalFoundries to support the development and expansion of facilities in Malta, NY, and Burlington, VT.

Last month, more multi-billion-dollar distributions were announced, including $8.5 billion for Intel to support investments across four states, (Chandler, AZ; Rio Rancho, NM; New Albany, OH; and Hillsboro, OR) to construct logic fabs, modernize advanced packaging facilities, and invest in R&D.

Along with Micron this month, $6.4 billion was allocated for Samsung to build an R&D facility, and advanced packaging fabs in Taylor, TX, and to expand a current-generation and mature-node facility in Austin, TX. And $6.6 billion was earmarked for TSMC to support the development of three greenfield leading-edge fabs in Phoenix, AZ.

Chip production, the supply-chain crisis, and the new law

In 2021, the decline in domestic chip production was exposed by a worldwide supply-chain crisis that led to calls for reshoring manufacturing to the US. After more than a year of work from the Administration to respond to acute semiconductor shortages, Congress in August 2022 passed the measure. With the CHIPS Act spurring them on, semiconductor makers including  Intel, Samsung, Micron, TSMC, and Texas Instruments unveiled plans for a number of new plants on US soil. (Qualcomm, in partnership with GlobalFoundries, also said it would invest $4.2 billion to double chip production in its Malta, NY facility.)

Companies became eligible In February 2023 to apply for the first round of CHIPS Act incentives totaling $39 billion for the construction of large-scale fabrication facilities. Last September, a second funding opportunity for small-scale fabrication projects opened.

The Commerce Department said the CHIPS ACT has moved extremely fast for a government program. For example, as part of the funding application process, the agency has received over 530 statements of interest from companies in 42 states. The department also received 120 pre-applications and full applications for funding.

The EU has given Apple just six months to open up iPads in the same way it’s been forced to open up iPhones in Europe. The decision follows an EU determination that the iPad — which leads but does not dominate the tablet market — should be seen as a “gatekeeper.”

Apple will not have much time to comply.

What’s really interesting, as noted by AppleInsider, is the extent to which the decision to force Apple to open up iPadOS seems to have been made even though the EU’s lead anti-competition regulator, Margrethe Vestiger, says the company doesn’t actually meet the criteria for enforcement. 

It doesn’t meet the threshold, so we’ll do it anyway

“Today, we have brought Apple’s iPadOS within the scope of the DMA obligations,” said Vestager.  “Our market investigation showed that despite not meeting the thresholds, iPadOS constitutes an important gateway on which many companies rely to reach their customers.”

This triumph of ideology is just the latest poor decision from the trading bloc and comes as Apple gets ready to introduce new software, features, and artificial intelligence to its devices at its Worldwide Developer’s Conference in June. 

With that in mind, I expect Apple’s software development teams need Europe’s latest decision about as much as the rest of us need an unexpected utility bill. That said, I imagine the challenge has not been entirely unexpected.

Sour grapes?

To some extent you have to see that Europe is playing defense.

Not only has it lost all advantages in space research to Big Tech firms such as Space X, but the continent has arguably failed to spawn a significant homegrown Big Tech competitor. This leaves Europe reliant on US technology firms, so it’s clear the EU is attempting to loosen the hold US firms have on digital business in Europe by using the Digital Markets Act is being applied.

The EU isn’t alone; US regulators are equally determined to dent the power Apple and other major tech firms hold. Fundamental to many of the arguments made is the claim that consumers will see lower prices as a result of more open competition, but I’m highly doubtful that will happen.

So, what happens next?

Apple will likely attempt to resist the EU call to open up the iPad, but will eventually be forced to comply. Meanwhile, as sideloading intensifies on iPhones, we will see whether user privacy and safety do indeed turn out to be compatible with sideloading.

In an ideal world, the EU would hold off on any action involving iPads pending the results of that experiment. It makes sense for regulators and Apple to work constructively together to protect against any unexpected consequences as a result of the DMA before widening the threat surface. 

Perhaps user security isn’t something regulators take seriously, even though government agencies across the EU and elsewhere are extremely concerned at potential risks. Even in the US, regulators seem to want us to believe Apple’s “cloak” of privacy and security is actually being used to justify anti-competitive behavior. 

Do the benefits exceed the risks?

Experientially, at least, there’s little doubt that platforms (including the Mac) that support sideloading face more malicious activity than those that don’t. Ask any security expert and they will tell you that in today’s threat environment, it’s only a matter of time until even the most secure systems are overwhelmed. So it is inevitable some hacker somewhere will find a way to successfully exploit Apple’s newly opened platforms.

It stands to reason that ransomware, adware, and fraud attempts will increase and it is doubtful the EU will shoulder its share of the burden to protect people against any such threats that emerge as a result of its legislation.

For most consumers, the biggest benefit will be the eventual need to purchase software from across multiple store fronts, and to leave valuable personal and financial details with a wider range of payment processing firms.

The joy I personally feel at these “improvements” is far from tangible.

Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.

Like many universities, Georgia Tech has been grappling with how to offer students the training they need to prepare them for a recent sea change in IT job markets — the arrival of generative AI (genAI).

Through a partnership with chipmaker Nvidia, Georgia Tech’s College of Engineering built a supercomputer dubbed AI Makerspace; it uses 20 Nvidia HGX H100 servers powered by 160 Nvidia H100 Tensor Core GPUs (graphics processing units).

Those GPUs are powerful — a single Nvidia H100 GPU would need just one second to handle a multiplication operation that would take the school’s 50,000 students 22 years to achieve. So, 160 of those GPUs give students and professors access to advanced genAI, AI and machine learning creation and training. (The move also spurred Georgia Tech to offer new AI-focused courses and minors.

Announced two weeks ago, the AI Makerspace supercomputer will initially be used by Georgia Tech’s engineering undergraduates. But it’s expected to eventually democratize access to computing resources typically prioritized for research across all colleges.

Computerworld spoke with Matthieu Bloch, the associate dean for academics at Georgia Tech’s College of Engineering, about how the new AI supercomputer will be used to train a new generation of AI experts.

The following are excerpts from that interview:

Tell me about the Makerspace project and how it came to be? “The Makerspace is really the vision of our dean, Raheem Beyah, and the school chair of Electrical and Computer Engineering (ECE), Arijit Raychowdhury, who really wanted to put AI in the hands of our students.

“In 2024 — in the post ChatGPT world — things are very different from the pre-ChatGPT world. We need a lot of computing power to do anything that’s meaningful and relevant to industry. And in a way, the devil is out of the box. People see what AI can do. But I think to get to that level of training, you need infrastructure.

“The name Makerspace also comes from this culture we have at Georgia Tech of these maker spaces, which are places where our students get to tinker, both within the classroom and outside the classroom. The Makerspace was the idea to bring the tools that you need to do AI in a way that’s relevant to do meaningful things today. So, right now, where we’re at is we’ve partnered Nvidia to essentially offer to students a supercomputer. I mean, that’s what it is.

“What makes it unique is that it’s meant for supporting students. And right now it’s in the classroom. We’re still rolling it out. We’re in phase one. So, the idea is that the students in the classroom can work on AI projects that are meaningful to industry — problems that are interesting, you know, from a pedagogical perspective, but they don’t mean a whole lot in an industry setting.”

Tell me a bit about the projects they’ve been working on with this. “I can give you a very concrete example. ChatGPT is a very typical, a very specific form of AI called generative AI. You know, it’s able to generate. In the case of ChatGPT, [that means] text in response to prompts. You might have seen a generative model that generates pictures. I think these were very popular and whatnot. And so these are the kind of things our students can do right now, …generate anything that would be, say, photo realistic.

“You need a pretty hefty computing power to train your model and then test that it’s working properly. And so that’s what our students can do. Just to give you an idea of how far we’ve come along, before we had the AI Makerspace, our students were relying largely on something called Google CoLab. CoLab is Google making some compute resources freely accessible for use. They’re really giving to us the resources they don’t use or don’t sell to their be clients. So it’s like the crumbs that remain.

“It’s very nice of them [Google] to do that, but you could only work with very [limited resources], say for training on something like 12,000 images. Now you can, for instance, train a generative model on a data set with like one million images. So you can really scale up by orders of magnitude. And then you can start generating these photo-realistic pictures that you could not generate before. That’s the most visual example I can give you.”

Can you tell me a little bit about the genAI projects the students are working on? How good is the technology at producing the results they want? “It’s a complicated question to answer. I mean, it has many layers. We’ve just launched it, like literally, the AI Makerspace was open officially two weeks ago. So right now it’s really used at scale in the classroom. The students in that class are learning how to do machine learning. [The students] have to get the data. [They] have to learn how to train a model. The students have homework projects, which consists of this fairly sophisticated model that they have to train, and that they have to test.

“Now we have a vision beyond that, what we call phase two of the Makerspace. We’re doubling the compute capacity. The idea now is that we’re going to open that to senior design projects. We’re gonna open that to something we call vertically integrated projects, in which are students essentially doing long-term research with faculty advisors over multiple years. Our students are going to do many things — certainly all of [the] engineering [school].

“We’ve given incentives to a lot of faculty to create a lot of new courses throughout the College of Engineering for AI and ML for what matters to their field. For instance, if you’re an electrical engineer, there’s a lot of hardware to it, you know you have a model for that. How do you make the model smaller so that you can put it in hardware? That’s one very tangible question that the students would ask. But if they’re, say, mechanical engineers, they might use it differently.  Maybe for them what generative AI could do is help them generate 3D models, think about structures that they would not think about naturally. And you can decline that model. The Makerspace is a massive tool. But how the tool is used is really a function of the specific domain. The goal, of course, is for Makerspace to be available beyond engineering.

“It’s already being used by our College of Computing, and we’re hoping that our co colleagues in, say, the College of Business will see the value, because they haven’t used AI yet — perhaps for financial models, predicting whether to sell or buy a stock. I think the sky is a limit. There’s no one use of AI through Makerspace. It’s an infrastructure that provides the tools. And then these tools find declinations in all different areas of expertise.”

Why is it important to have this technology at the school for students to learn about AI? “The way we’ve come to articulate this is as follows: We’re not deliverers in doomsday scenarios, where AI is going to generate terminators that are going to eradicate humanity. Okay, that’s not how we’re thinking about it.

“AI is definitely going to change things. And we think that AI is certainly going to displace a few people. I think the humans enhanced by AI will start displacing humans who don’t use AI.

“I think the way a lot of the discussion has been shaped since ChatGPT was released to the world, in universities there’s sometimes a lot of fear. Are students cheating on their essays? Are students cheating on this cheating on that? I had these discussions with my colleagues in computing. We have an intro to computing class, where they’re cheating to write their code, which I think is not the right approach to it. But, the devil is out of the box. It’s a tool that’s here, and we have to learn how to use it.

“If I can give you my best analogy: I drive my car. I don’t know how my car really works. I mean, I was never a mechanical or electrical engineer. I sort of know what it takes [for a car to run], but I’m unable to fix it. But that doesn’t mean I can’t drive it. And I think we’re at that stage with AI tools, where one needs to know how to use them because you don’t want to be the person riding a bicycle when everybody else has a car.

“Not everyone needs to be a mechanic, but everyone needs a car. And so I think we want every student at Georgia Tech to know how to use AI, and what that means for them would be different depending on their specialty, their major. But these are tools, and you need to have played with them to really start mastering them.”

In what way has AI expanded Georgia Tech’s curriculum? “We were lucky in the sense that [we’re] building that infrastructure from new. But thinking about AI, Georgia Tech has been doing it for decades. Our faculty is very research focused. They do state-of-the-art research and AI…was always there in the background — the roots of AI. We had a lot of colleagues who actually were doing machine learning without saying it in these terms.

“Then when deep learning started appearing, people were ready to grasp that. So, we were already thinking about doing it in the labs, and the integration in the curriculum was already slowly happening. And so what we decided to do was to accelerate that so the Makerspace…accelerates the other mechanisms we’ve had to give incentives to faculty, to rethink the curriculum with AI and Ml in mind.”

So what AI courses have you launched? “I can give you two examples that we’ve launched, which are, you know, very new. But I I think I’ve been quite successful already. One is we’ve officially launched an AI minor.

“The great thing about this AI minor [is that it] is a way for students to take a series of courses with a coherent and unified team, and they get credit for that on their diploma and their transcript. This minor was designed as a collaboration right now between the College of Engineering and the College of Liberal Arts.

“Then we have the ethics and policy piece. Students need to take a specially designed course on AI Ethics and AI policy. We’re thinking very holistically. AI is a technology play, but if you just train engineers to do the technology piece alone, maybe then the doomsday-Terminator scenario is a likely outcome.

“We want our students to think about the use of AI because it’s technology that can have many uses [and problems associated with it]. We talk about deep fakes. We’re worried about it for all sorts of political reasons.

“The other thing we’ve done in the College of Engineering is essentially incentivized faculty to create new undergraduate courses related to AI and ML but relevant to their own disciplines. I literally [just made the announcement] and the has college approved 10 new courses or significantly revamped courses. So, what that means is that we have courses on machine learning for smart cities, civil environmental engineering, and a course in chemical processes in chemical and bioengineering, where they’re using AI and ML for completely different things. That’s how we’re thinking of AI. It’s a tool. So the courses need to embrace that tool.”

Are students already using genAI to assist in creating applications — so software engineering and development? “Officially or unofficially? I don’t have a good answer, because the truth is, I don’t know. But what I know is that our students are using it with or without us. You know they are using generative AI because I’m willing to bet they all have a subscription to ChatGPT.

“Now in the context of the Makerspace, this is a resource you can start doing all sorts of things. Our students are using it to write lines of code absolutely.”

So what would you say is the most popular use right now of the AI Makerspace? “We haven’t officially launched it at scale for very long, so I can’t attest to that. It’s been used largely in the classroom setting for the kind of homework students could not even dream of doing before.

“We’re going to launch it and use it over the summer for an entrepreneurship program called Create X, that students can use to take ideas and go through prototype and potentially think about building startups out of these. So that’s going to be primary use over the summer, and we’re testing it over these few weeks in the context of a hackathon in partnership with Nvidia, where teams come with big problems that they want to solve. And we want to accelerate their science, to use Nvidia’s words, to by teaching them how to use that Makerspace.”

Dropbox now offers end-to-end encryption and key management for customers on certain paid plans, part of a range of updates to the file sharing application announced this week. 

Customers files are already encrypted “at rest” using 256-bit Advanced Encryption Standards, said Dropbox, but the end-to-end encryption integrated into team folders offers an added layer of security. 

The change means that only the sender and recipient can access content, with “not even Dropbox” able to view customers files, the company said in a blog post Wednesday. 

Dropbox said it will also provide customers with access to encryption keys, managed by FIPS 140-2 Level 3 key management services.

Information on how to activate and manage team folder encryption is available on the Dropbox website. The company warned that end-to-end encryption restricts certain features in the app, such as the ability to share files with users outside of a team, and might not be suitable for all files stored in a Dropbox account.

Other security features include the ability to manage team membership and invites from the Dropbox admin dashboard, and an updated Trust Center that contains security and compliance information related to Dropbox products. 

The security features are now available to customers on Dropbox Advanced, Business Plus, and Enterprise plans.

Dropbox announced several other new features as part of the latest release.

It will be easier to collaborate with colleagues on certain Microsoft files from within the Dropbox application, with a co-authoring feature that lets multiple users edit Word, Excel, and PowerPoint documents at the same time. Users can also see who’s working on a document and any edits made in real-time. (That feature is currently in beta.)

There’s also an integration between Dropbox Replay and Microsoft OneDrive, which lets users pull files from Microsoft’s file storage platform into the video and audio collaboration tool more easily for reviews and approvals. 

Dropbox Replay will also get new features, including the ability to review and approve additional file types such as PDF and PSD files, integration with music production application Avid Pro Tools, and dynamic watermarking to help protect proprietary content.

Other updates include changes to the Dropbox’s website UI, following a revamp last October. The new capabilities let users preview files more easily, pin favorite files to the navigation bar, and access suggest quick actions for files.