No software project gets very far without the means to plan, communicate and track work. Developer collaboration tools must provide ways to track and assign tasks, work together on software, report progress and share code among team members. Otherwise, you have a bunch of developers, not a development team.

Key categories of developer collaboration tools include project management, communication and code collaboration tooling. Let's explore each tool category to understand how developers collaborate.

Notable examples of project management software tools include:

Developers on a project team must track and manage work. Work can include tasks as well as issues to resolve. Project management tools should give developers a system to organize work itself: what work is completed, what tasks are behind and where task dependencies exist. This type of developer collaboration tool can also visualize information about the work a development team needs to do, via diagrams like Gantt, PERT and burn down charts.

The following project management tools address these needs and offer basic functionalities, such as privacy settings and team member tagging.

Jira. This Atlassian tool is designed for Agile adopters. The tool facilitates sprint planning, user story management and more. With Jira, a development team can view a project on a roadmap, Kanban board and to-do list.

Jira includes a healthy list of product integrations via the Atlassian Marketplace, which can provide options not available natively, such as a tool for a calendar view. Jira includes prebuilt workflows for Trello and also connects with other Atlassian tools like Confluence and Bitbucket.

Trello. Trello, another Atlassian product, breaks down projects into Kanban boards; each board into lists; and each list into a set of cards. In a typical example, a board has lists that represent a different step in a development team's workflow, and each list's cards are descriptions of specific tasks. Developers can move a card from one list to another to indicate it's ready for the next stage. They can add details, files, due dates and comments to each card.

Asana. Asana can display work in various formats including checklists, a timeline and Kanban boards. Asana offers an out-of-the-box calendar view. Asana's checklist/to-do list functionality lets users create subtasks, attach files to tasks and add category tags.

Airtable. Airtable enables developers to look at a project's work in progress in a spreadsheet interface, calendar format, visual-centric gallery and Kanban board format. Additionally, the vendor has a low-code/no-code tool, Airtable Apps, available at the pro pricing tier to augment a team's dashboard. Prebuilt app templates are available.

Smartsheet. The Smartsheet platform emphasizes its grid -- i.e., spreadsheet -- to provide a 30,000-foot view into projects and ongoing work. The product also provides Kanban card, calendar and Gantt chart view options. Smartsheet dashboards offer a look at crucial metrics.

Monday.com. This product uses the term pulses, in place of tasks, to describe work. Monday.com is otherwise similar to other project management tools -- users can assign a status, deadline and dependencies to a team member for each pulse. Monday.com has far fewer integrations than other project management tools. Managers could find this tool to be a good choice to see what team members' respective workloads look like.

The list of communication tools a development team could use includes:

Constant emailing back-and-forth is a disorganized and inefficient way for team members to communicate. With the proliferation of remote and globally distributed work, it's not often feasible to walk over to a co-worker's desk or schedule an in-person meeting. Developers need capable and user-friendly communication tools.

Slack. Slack is a messaging platform that supports conversations across multiple channels and via direct message. Users can log onto their organization's Slack workspace via a browser, desktop application or mobile app.

Organizations often create channels for different teams, initiatives or projects -- only for the team members involved in that particular group. Channels can be public or private. Slack also offers audio and video calling, as well as screen sharing functionality.

Developers can program Slack bots to perform a number of functions. For example, Slack bots can share links or files when team members type a specific command.

Slack directly integrates with a variety of applications -- Google Drive, OneDrive, Google Calendar, Outlook, Gmail, GitHub, Trello, Asana, Jira and Zoom are just a few.

Teams. Microsoft Teams is a channel-based messaging platform that allows group chats and direct message conversations. Teams works in a desktop browser, in a downloaded app or on a mobile device.

Each Teams chat tracks the files uploaded in a channel, and users can simultaneously edit Word docs, Excel spreadsheets and other files directly in Teams. Additionally, Teams has video chat functionality with features like screen sharing and hand raising.

The list of Microsoft Teams integrations includes Box, Asana, Smartsheet, Jenkins, Trello, Jira, GitHub and Zoom.

Google Meet. Google Meet is a business video conferencing tool. Google Meet is free until March 31, 2021. After that grace period, non-enterprise accounts will have a 60-minute time limit. However, Google Meet lacks features like breakout rooms and hand raising. Also, the service requires each user to have a Google account.

Zoom. Zoom has standard features for a video conferencing app, including webinar capabilities, live chat, recording capabilities, screen-sharing and breakout rooms. Plus, attendees don't need an account to join a Zoom meeting. Zoom has paid and free options. Any meeting on the free version of Zoom with three or more people has a 40-minute time limit.

Developers can choose from code collaboration or version control tools, such as:

To do programming on a group project, developers need a place to store code and juggle contributions to a single codebase coming from multiple people. A version control system enables developers to perform various actions, including check out code, fork a repository, create a branch, merge code changes and pull others' changes. Additionally, a version control tool keeps a history of the changes made to a codebase.

GitHub. This code-hosting service allows multiple developers to work on the same application at once. Respondents to Stack Overflow's 2020 Developer Survey said they used GitHub more than any other collaboration tool, including Slack, Jira and Google Suite.

GitHub integrates with several app-dev platforms and numerous programming languages. Add-ons are available for most project management or communication tools. GitHub offers free unlimited public and private repositories for an unlimited number of collaborators, as well as paid versions for additional storage, security and automation support. GitHub also has features for dev and project management.

GitLab. GitLab is another prominent service that hosts repositories. The open source tool provides Git-based code hosting, CI/CD functionalities, wiki features and issue tracking. GitLab provides access to an unlimited number of collaborators, and both public and private repositories. However, the tool's free tier lacks some dashboard features, business support, multi-region accessibility and compliance automation, which are provided in paid tiers.

Bitbucket. One of the draws of the Bitbucket repository hosting service is the built-in integration with other Atlassian tools like Jira. Bitbucket allows developers to organize repos into projects, which can help dev team members stay on task. Bitbucket's free plan offers an unlimited number of private repositories, but Atlassian caps it at five developers. Bitbucket's standard pricing tier of $3 per user each month is Atlassian's cheapest paid option and allows for an unlimited number of developers.

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Harness these three types of developer collaboration tools - TechTarget

I've written a lot of blog posts here on Gamasutra about the design decisions and implementation choices we have made in our game engine: The Machinery. So I'm happy to announce that The Machinery is now in Open Beta, available for anyone to download and try out.

The download includes all the engine APIs, headers, and docs, so you can see how a lot of the stuff I've written about here works in practice. For example, check out foundation/carray.inl and foundation/hash.inl to see our type-safe C implementations of arrays and hash tables, that I talked about in the MinimalistcontainerlibraryinC blog post. Or foundation/slab.inl for a similar implementation of the bulk data storage model that I talked about in the DataStructuresPart1:BulkData post.

If you run into any problems with the download or have requests for specific features, post them to our issue tracker. For more general discussions and help getting started, we have a forum. You can also chat with us on our Discord server. You will find us there every now and then, but well pay special attention on Thursdays.

If you haven't heard about it before, The Machinery is a new lightweight and flexible game engine, designed to give you all the power of a modern engine in a minimalistic package that is easy to understand, extend, explore, rewrite, and hack. Beyond games, the API can also be used for simulations and visualizations as well as building custom tools, editors, and applications.

Some of the things that make The Machinery more hackable than other game engines are:

Some of the features currently available in The Machinery are:

Finally, here is some user-created content from The Machinery. Happy hacking!

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Niklas Gray's Blog - The Machinery Goes Open Beta - Gamasutra

One of the most interesting projects to watch these days in tech is RISC-V. The nonprofit organization and wider community is building an open-source and standardized instruction set architecture (ISA) that allows chip creators to design their own chips unencumbered by licensing and patents typical of other ecosystems, such as those of Arm.

Building an ISA and the associated tooling is hard work and expensive, which is one reason why the industry has been practically impervious to the open-source movement that is now a mainstay in software circles. The RISC-V community has spent years developing, cohering and getting traction for its vision of the future of computing. Along the way, its acquired major support, with members as diverse as Google, Oculus, Huawei, IBM, Nvidia (which is in the process of buying Arm), Qualcomm and more joining the organization.

Now, the ecosystem is starting to mature and is getting ready for wider adoption outside of hardware laboratories and test data rooms.

SiFive is one of the most high-profile companies spearheading the commercialization of RISC-V technology. It was founded by a number of the inventors and leading researchers of the technology (which was centered around Berkeley), and has also managed to attract big names like Chris Lattner, who led the development of the Swift programming language that today is the main choice for developers in the Apple ecosystem. The company has raised $190 million to date, including most recently a $61 million Series E round. Among its most notable investors is Sutter Hill, which made a massive return earlier this year on Snowflake Computing.

Today at the Linley Conference, a major stop on the circuit for processor announcements, SiFive launched its PC-focused RISC-V board, dubbed Unmatched. The goal of the product is to make it easier for developers to buy PCs or host server farms and enable them to test their code on RISC-Vs architecture. That should make the onramp into the RISC-V universe more inviting for a broader range of engineers.

Its all part of a revamped go-to-market strategy that SiFives new CEO Patrick Little is plowing ahead on. Little joined the company last month from Qualcomm, where he led the companys expansion into automotive tech, and he has a multi-decade background in the industry. His mandate is to take the technological work that SiFive has developed and get it into the hands of the widest number of users.

Were just trying to drive adoption and open up the platform, so that software can be developed at scale, Little said. He noted that developers have consistently asked for a more mainstream PC board in a standard form factor. They wanted to plug and play on a PC platform that was familiar to them, he said.

The HiFive Unmatched PC board hosts the SiFive FU740 SoC, and has a five-core processor that is based on SiFives 7-series core, which the company says is the fastest commercially available core available through RISC-V today. The board is based on the mini-ITX form factor.

In addition to the PC board, the company announced last week at the Linley conference the launch of its SiFive Intelligence VIU7 Series, which is a vector processor designed for AI and graphics workflows and is centered around the RISC-V Vector Extension (RVV) standard ISA.

These announcements are laying the groundwork for more new products targeting the major buckets of computing needs in the industry.

One major new propulsive force for the company is indeed Nvidias announcement that it intends to acquire Arm. That news reverberated quickly around the industry as chip builders grapple with a future where the tie-up controls a wide swatch of the AI, graphics and mobile processing markets. More and more companies are looking for alternatives, and RISC-V is one of the few available on the market today.

An open-source ISA means a company can design around that platform for years or even decades to come without the fear that it would go away, Little said. Its moved from an operational objective to a strategic imperative.

Little is ambitious for SiFive, saying that leading is choosing for us, because the opportunity is fantastic right now, and so really its just trying to map these assets into the right opportunities. With the market currents going its way and open-source hardware looking less like a pipe dream, SiFive is well-positioned to take advantage of what might well be one the bigger shifts in processing we have seen in years.

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SiFives new PC is bringing open-source computing closer to reality - TechCrunch

The Red Hat-sponsored Fedora Project has released its latest Linux distribution, Fedora 33.

Image: Fedora

Red Hat's community-driven Fedora Project has released the latest version of its open-source Linux distribution, Fedora 33.

The latest version of Fedora Workstation is designed for developers who want a desktop Linux setup that requires minimal configuration and "just works", according to Fedora Project Leader, Matthew Miller.

At the same time, Fedora 33 introduces new features for Fedora IoT and includes updated key programming languages and system library packages, including Python 3.9, Ruby on Rails 6.0 and Perl 5.32.

"At the heart of Fedora, we aim to deliver a free, innovative, open source platform for hardware, clouds and containers that is easy to use no matter where you're starting," said Miller.

SEE: Linux commands for user management (TechRepublic Premium)

"Fedora 33 delivers on that promise with updates targeted at both a new and advanced user, while keeping new and exciting use cases in mind like edge computing and IoT for continued innovation."

Among the key cosmetic changes to Fedora 33 is an update to the GNOME desktop environment. GNOME 3.38 introduces improvements to performance and stability, and sports new features such as the Tour application, which serves as an introduction to GNOMES's main features for new users.

For more advanced users, the new Boxes feature supports the editing of virtual machine libvirt XML attributes directly, allowing developers to modify deeper settings that aren't available in the user interface.

Another significant change is the shift to b-tree filing system (BTRFS) as Fedora's default filesystem. With this, Red Hat says, users get a more stable and mature copy-on-write file system offering modern features like better data integrity, transparent compression and multiple device support. Only core features are being made available initially, but Red Hat suggests that further enhancements will be built into future releases.

SEE: Top 5 programming languages for systems admins to learn (free PDF) (TechRepublic)

For IoT and Edge use cases, Fedora 33 IoT introduces the Platform AbstRaction for SECurity (PARSEC), an open-source initiative designed to provide a common, platform-agnostic API for hardware security and cryptographic services.

Fedora 33 also makes nano the default text editor, while in Fedora KDE, the Fedora 33 continues the work of Fedora 32 Workstation by having the EarlyOOM service turned on by default. EarlyOOM works by checking the amount of available memory and killing processes to improve performance in low-memory situations.

Fedora 33 can be downloaded at https://getfedora.org/. In the meantime, you can check out TechRepublic's initial hands-on impressions here, courtesy of Jack Wallen.

You don't want to miss our tips, tutorials, and commentary on the Linux OS and open source applications. Delivered Tuesdays

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Fedora 33: This new Linux distribution is designed to 'just work' - TechRepublic

Transportation

Other cities are turning car-free roads into outdoor destinations this year. Why can't we?

NEW YORK, NEW YORK JULY 26: A No thru traffic, open streets: restaurants sign is seen near an inflatable elephant in DUMBO, Brooklyn. (Photo by Alexi Rosenfeld/Getty Images)

A pop-up movie theater on a side street in Harlem. A touch-less obstacle course for kids in the Bronx. A five-week-long stationary parade in Chicago. Outside Boston, cities have been turning their streets into getaways and gathering places, closing off underused roadways to car traffic and turning them into open-air markets, or setting up workstations for students to use while going to school remotely.

And frankly, Im feeling jealous.

Back at the beginning of the pandemic, I imagined wed see a revolution in how we treat streets in Boston, at least temporarily. But while we have seen some some very cool things this summer and fall, like new protected bike lanes and outdoor restaurant patios, the city has fully closed very few streets.

Through a spokesman, Bostons transportation department says it is open to considering street closures in the new year, but for now was more focused simply on helping restaurants and other businesses use space on sidewalks and along curbs. If we really want to give Bostonians more incentive to get outside this winter than chilly restaurant patios, though, time is running out to get creative. Its not just about providing a break from the work-from-home doldrums, or giving us a safe activities to do at a time when cases are spiking heremuch as well need both. Closing down streets and filling them with fun wintry things to do could also provide a needed boost to local businesses that are starving for attention this year.

Take Frisco, Colorado, for example, where a Main Street was converted into a full-on pedestrian thoroughfare, complete with yard games and a mini-golf course. Or Harlem, where a closed street gave neighbors space to throw a socially distanced block party, complete with a pop-up outdoor movie theater. Or look to Denver, where, after the cancellation of its popular wintertime Parade of Lights, officials opted to display stationary floats in the middle of the city during November and December, giving people the chance to walk around and see them on their own time. All great ideas that will get people out of their homes.

Street closed to traffic. Pandemic-era neighborhood party. pic.twitter.com/Nj3qSvDX4D

Kevin Stankiewicz (@kevin_stank) October 18, 2020

Even with everything else going on in the city right now, doing something similar in Boston would not be a heavy lift on the citys part, and would rely primarily on community groups stepping up. Thats according to Leslie Davol, co-founder of a New York-based nonprofit called Street Lab, which has been bringing kid-friendly programming to NYC streets this summer, including a no-touch obstacle course, community chalk-drawing events, and a WiFi-enabled homework hub for students to safely complete schoolwork in the outdoors. New Yorks so-called Open Streets program, which set aside 100 miles of car-free streetscapes back in July, hasnt been perfect, Davol says. Some drivers are upset about losing parking, and some of the officially designated Open Streets in the city have languished without anything special happening on them. The city has largely left programming up to volunteers and community groups. But when theyve thrived, they have successfully encouraged people to safely congregate in the fresh air.

Boston should definitely do it, Davol says. There are a bunch of streets that are working beautifully here and theyre gorgeous. Weve seen a beautiful flowering of community spirit of people coming out and doing whatever it takes to reclaim the street.

Activate the street all weekend. Today, well deploy the no-touch obstacle course and our street marker kit on Pleasant Ave in East Harlem. Thanks @ridespin, @NYC_DOT, @NYCommTrust, and @uptown_grand, showing how how New Yorkers can come together, safely. https://t.co/g6jcszIdB7 pic.twitter.com/LaW3AwWHt2

Street Lab (@streetlab) October 18, 2020

Jonathan Berk, a Boston-based placemaking consultant and founder of a crowdfunding platform called Patronicity, is hoping Bostons 20 Main Streets districts might be interested in taking on that role here. Earlier this year, he launched an initiative called Winter Places, which solicited ideas for reclaiming streets in the colder months ahead. In all, 65 submissions came in from both in Boston and around the world, among them proposals to plop outdoor fire pits in the street, set up open-air markets filled with pushcarts, or build Christmas mazes made of evergreen trees lighting the path to open storefronts. The recommendations have been compiled into an open-source online guidebook.

Warm outdoor dining spaces WITHOUT propane.Take a vacation and explore your hometown main street. Winter warming stationsA Maze of holiday trees to encourage visitors to explore downtown.

These ideas and more in the #WinterPlaces guide https://t.co/zfmduaYj5E pic.twitter.com/YsHjPE29gq

Jonathan Berk (@berkie1) October 26, 2020

I think whats lacking in the city right now is an opportunity to create more wide-scale open streets, and I think thats going to be necessary to continue the success of outdoor commerce in the winter months, Berk says. Every neighborhood Main Street district should have the opportunity to have some event space or open street space to kind of get creative, bring people back, and have some space to socially distance.

Improvements may not need to be that complicated, though, or that flashy. Stacy Thompson, head of Bostons LivableStreets Alliance says. She suggests a citywide effort to get cars off the streets and into underused parking lots in places like YMCAs and libraries that would free up more space for outdoor social gatherings, and make them more navigable for bikers and pedestrians, thus coaxing more people out of their homes.

People think we need to create a festival, we need to program something to get people outside, Thompson says. People want to go outside. Its about just giving them the space, and the ability to get there in the first place.

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How Boston Could Save Winter by Finally Doing Something Fun with Its Streets - Boston magazine

At Bytecode Alliance's first anniversary, WebAssembly developers Lin Clark and Till Schneidereit announced in a blog post that Fastly has acquired part of the WebAssembly (Wasm) team from Mozilla. Going forward, Mozilla will continue to focus on Wasm-in-the-browser, especially in the Firefox browser. Fastly, on the other hand, will take stewardship within Bytecode Alliance for Wasm-on-the-server, including Fastly's own commercial WebAssembly serverless offerings Compute@Edge. That arrangement also resulted in the merger of Mozilla's wasmtime and Fastly Lucet Wasm VM projects. Lucet and wasmtime already share many codebases, and this merger ensures that their future developments will continue on the same path.

In the blog post, Clark and Schneidereit laid out their technology vision for the future of Wasm-on-the-server. Core to their vision is the nanoprocess model, which provides a secure and lightweight container for Wasm programs yet still makes it easy for sandboxed Wasm programs to communicate with each other and with the rest of the system.

Technically, there are three proposed enhancements to Wasm on the critical path to the nanoprocess.

The first enhancement is the WebAssembly Systems Interface (WASI), which provides a way for Wasm programs to call standard libraries functions in the host system. On the server-side, it means access to the file system, environment variables, random numbers, and sockets. WASI is now supported across multiple leading Wasm implementations.

WASI implementations vary in their completeness and performance. For example, Google's V8 uses the host environment's JavaScript runtime as a proxy for operating system access and hence is slow.

The WASI approach is not limited to operating system standard library access. The blog post discussed additional WASI-like extensions Bytecode Alliance is championing, such as wasi-socket and wasi-nn. Beyond the Bytecode Alliance, there are also many initiatives to give Wasm access to more host functions. For example, in the blockchain world, the Ethereum flavored WebAssembly (Ewasm) is a form of WASI that gives Wasm access to the host Ethereum blockchain's user accounts and transaction services.

The second enhancement is the Interface Types proposal, which enables Wasm programs to communicate with external programs, either in the host operating system or in the language runtime that embeds Wasm (eg, Node.js). This proposal is still in its early stage and does not yet have support from the compiler toolchain. However, it is already supported in wasmtime and Second State VM. The goal is to make Wasm programs more powerful and more embeddable.

Taken together, WASI and Interface Types make it easy for developers to fully take advantage of the native host system while preserving the security of the Wasm sandbox. An early example is Second State VM's work on providing native GPU access to its Wasm programs for tensorflow model inference.

The third element of the nanoprocess is module linking, which allows Wasm programs to call each other in addition to calling host functions. The ability to declare module dependencies could enable public package management systems similar to Node.js's NPM and Rust's Crate.io. It could complement the WAPM work Wasmer already started.

This latest blog post see Bytecode Alliance laying out a concrete vision for wasm-on-the-server. At the same time, the Wasm open-source community is now much larger than the corporations in Bytecode Alliance alone. There are multiple Wasm VM implementations, complier toolchains for programming languages, as well as host Operating Systems and environments (e.g., Node.js, Deno, or blockchains).

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Bytecode Alliance Lays Out Plans for WebAssembly on the Server-side - InfoQ.com

photo by Kate Nuelle

Local art venues like the San Antonio Museum of Art (SAMA) and Artpace San Antonio have been anxious to re-open their doors to the public to ensure that creators and SA citizens alike could re-kindle their passions for art. When the COVID-19 pandemic first hit in mid-March, local directors at these organizations worked tirelessly towards making certain that their respective venues would operate as best as they could while remote. Once social distancing guidelines and ordinances allowed businesses and organizations to re-open their doors, SAMA and Artpace have both made adjustments to their previous operations and have since opened their doors back up to the public.

milie Dujour, P.R. and Digital Communications Manager at SAMA, describes the work that went on during the period of the pandemic where social distancing and quarantining were both very strict.

You can actually register online on our website and go on different [online] tours and view artist [documentaries] and other stuff. We also created a page on our website that listed a bunch of digital things that people could do, Dujour said.

Once purely online procedures morphed into work to re-open the museum, workers quickly implemented sanitation practices and hour shifts to invite the public to view exhibits again. In addition to opening the exhibits, SAMA will also be offering daily screenings.

We train our staff about cleaning highly-touched surfaces everywhere, Dujour said. We also created a way for our visitors to get their tickets online, so they dont have to interact with the staff.

Similarly, Artpace San Antonio worked very diligently to create remote work for employees, interns and artists when the pandemic had first hit. Founded in 1995, Artpace has always operated as an organization that invited national and international artists to reside here in San Antonio, where they can showcase their art. Once the pandemic hit, they were forced to quickly decide how they could continue to support national and international artists.

We didnt want to eliminate any opportunities, said Riley Robinson, Director at Artpace. [Programs] arent canceled but postponed for a year. We simply couldnt get them here.

Despite having to postpone many events, the Artpace team worked on ensuring that people could still engage in activities at Artpace during the summer. They offered online exhibits, book clubs and internships for high school and undergraduate students. It was important to them that they still connect with the community.

We switched to a virtual platform. It was a way to keep connecting with the public and provide some source of educational and art-related material through our website, said Ashley Mireles, Artpaces Education Coordinator.

Despite COVID-19 uncertainty, both organizations have seen opportunities to keep some of their new practices in motion to create more accessibility for the public in a post-pandemic future.

At SAMA, for example, virtual programming has provided great opportunities for the public to engage in art and education while at home.

We want to be able to offer more videos and more digital things online, our social media channels and our YouTube channel. Our mission is to share our collection and to continue inspiring people, Dujour said.

Artpace has spent a lot of time perfecting their social media outreach as well as their website to include programming that is accessible to those who arent able to visit in-person.

Moving forward, having seen how were able to even reach more people through having things like virtual programming, Instagram Lives and other things that our communications team does is really cool to see. Were able to keep a lot of things going and extend our reach, you know, Mireles said.

Artists, art directors and other local art workers alike have all been working rigorously to bring art back to the public during a time where community like this may seem lost.

Artists are resilient. Theres a lot of people in need of help, and frankly, the country is kind of tenuous at the moment. Weve been working with compassionate flexibility towards our public, Robinson said.

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Exploring the afterlife of San Antonio's art organizations - The Trinitonian

Machine learning and AI continue to reach further into IT services and complement applications developed by software engineers. IT teams need to sharpen their machine learning skills if they want to keep up.

Cloud computing services support an array of functionality needed to build and deploy AI and machine learning applications. In many ways, AI systems are managed much like other software that IT pros are familiar with in the cloud. But just because someone can deploy an application, that does not necessarily mean they can successfully deploy a machine learning model.

While the commonalities may partially smooth the transition, there are significant differences. Members of your IT teams need specific machine learning and AI knowledge, in addition to software engineering skills. Beyond the technological expertise, they also need to understand the cloud tools currently available to support their team's initiatives.

Explore the five machine learning skills IT pros need to successfully use AI in the cloud and get to know the products Amazon, Microsoft and Google offer to support them. There is some overlap in the skill sets, but don't expect one individual to do it all. Put your organization in the best position to utilize cloud-based machine learning by developing a team of people with these skills.

IT pros need to understand data engineering if they want to pursue any type of AI strategy in the cloud. Data engineering is comprised of a broad set of skills that requires data wrangling and workflow development, as well as some knowledge of software architecture.

These different areas of IT expertise can be broken down into different tasks IT pros should be able to accomplish. For example, data wrangling typically involves data source identification, data extraction, data quality assessments, data integration and pipeline development to carry out these operations in a production environment.

Data engineers should be comfortable working with relational databases, NoSQL databases and object storage systems. Python is a popular programming language that can be used with batch and stream processing platforms, like Apache Beam, and distributed computing platforms, such as Apache Spark. Even if you are not an expert Python programmer, having some knowledge of the language will enable you to draw from a broad array of open source tools for data engineering and machine learning.

Data engineering is well supported in all the major clouds. AWS has a full range of services to support data engineering, such as AWS Glue, Amazon Managed Streaming for Apache Kafka (MSK) and various Amazon Kinesis services. AWS Glue is a data catalog and extract, transform and load (ETL) service that includes support for scheduled jobs. MSK is a useful building block for data engineering pipelines, while Kinesis services are especially useful for deploying scalable stream processing pipelines.

Google Cloud Platform offers Cloud Dataflow, a managed Apache Beam service that supports batch and steam processing. For ETL processes, Google Cloud Data Fusion provides a Hadoop-based data integration service. Microsoft Azure also provides several managed data tools, such as Azure Cosmos DB, Data Catalog and Data Lake Analytics, among others.

Machine learning is a well-developed discipline, and you can make a career out of studying and developing machine learning algorithms.

IT teams use the data delivered by engineers to build models and create software that can make recommendations, predict values and classify items. It is important to understand the basics of machine learning technologies, even though much of the model building process is automated in the cloud.

As a model builder, you need to understand the data and business objectives. It's your job to formulate the solution to the problem and understand how it will integrate with existing systems.

Some products on the market include Google's Cloud AutoML, which is a suite of services that help build custom models using structured data as well as images, video and natural language without requiring much understanding of machine learning. Azure offers ML.NET Model Builder in Visual Studio, which provides an interface to build, train and deploy models. Amazon SageMaker is another managed service for building and deploying machine learning models in the cloud.

These tools can choose algorithms, determine which features or attributes in your data are most informative and optimize models using a process known as hyperparameter tuning. These kinds of services have expanded the potential use of machine learning and AI strategies. Just as you do not have to be a mechanical engineer to drive a car, you do not need a graduate degree in machine learning to build effective models.

Algorithms make decisions that directly and significantly impact individuals. For example, financial services use AI to make decisions about credit, which could be unintentionally biased against particular groups of people. This not only has the potential to harm individuals by denying credit but it also puts the financial institution at risk of violating regulations, like the Equal Credit Opportunity Act.

These seemingly menial tasks are imperative to AI and machine learning models. Detecting bias in a model can require savvy statistical and machine learning skills but, as with model building, some of the heavy lifting can be done by machines.

FairML is an open source tool for auditing predictive models that helps developers identify biases in their work. Experience with detecting bias in models can also help inform the data engineering and model building process. Google Cloud leads the market with fairness tools that include the What-If Tool, Fairness Indicators and Explainable AI services.

Part of the model building process is to evaluate how well a machine learning model performs. Classifiers, for example, are evaluated in terms of accuracy, precision and recall. Regression models, such as those that predict the price at which a house will sell, are evaluated by measuring their average error rate.

A model that performs well today may not perform as well in the future. The problem is not that the model is somehow broken, but that the model was trained on data that no longer reflects the world in which it is used. Even without sudden, major events, data drift can occur. It is important to evaluate models and continue to monitor them as long as they are in production.

Services such as Amazon SageMaker, Azure Machine Learning Studio and Google Cloud AutoML include an array of model performance evaluation tools.

Domain knowledge is not specifically a machine learning skill, but it is one of the most important parts of a successful machine learning strategy.

Every industry has a body of knowledge that must be studied in some capacity, especially when building algorithmic decision-makers. Machine learning models are constrained to reflect the data used to train them. Humans with domain knowledge are essential to knowing where to apply AI and to assess its effectiveness.

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5 machine learning skills you need in the cloud - TechTarget

By James H. Lee

The view is always better from the edge. In this new column for Delaware Business Now, Ill cover new technologies and growth investments. As a professional futurist, I keep my finger on the pulse of change. My background as a financial analyst helps me to distinguish between hype and opportunity.

This month, Id like to cover an emerging technology with an enormous generational divide cryptocurrency. Never before have I seen anything create such excitement for young traders while generating complete confusion amongst experienced investors.

When Bitcoin was introduced to the world in 2009, it was built on an entirely new technology known as the blockchain.

A blockchain is simply a distributed public history of transactions. Each new transaction adds another link to the chain. Those transactions are stored anonymously on thousands of computers. It is a secure network, because in order to break into it to change the records, you would need to hack all the nodes simultaneouslyprovided that you can even find them. New bitcoins were issued to miners for their services in verifying new transactions as they appeared on the blockchain. As the system grew in complexity, more bitcoins were gradually introduced into circulation. In this way, the blockchain paid for its own maintenance.

There are at least four breakthroughs that happened here:

Breakthrough #1: The introduction of an entirely new form of money

Cryptocurrencies are a computational store of value. Instead of being backed by gold or the taxing authority of a government, cryptocurrencies are only as useful as their software code. They have the advantage (or disadvantage) of being almost entirely unregulated. As such, crypto can also be transferred much more quickly than conventional money. Because the amount of currency being introduced into the system is predetermined via algorithm, some have a limited supply and may be better able to maintain value over time. Others may quickly become obsolete.

Breakthrough #2: The same technology used to track the movement of Bitcoin could be used as a secure means to track the change of ownership of any other asset, physical or digital

This means that the chain of ownership for anything could be tracked using blockchain technology as a way that is resistant to hacking and forgery.

Joi Ito of the MIT Media Lab says, My hunch is that The Blockchain will be to banking, law and accountancy as The Internet was to media, commerce and advertising. It will lower costs, disintermediate many layers of business and reduce friction. As we know, one persons friction is another persons revenue.

Some of the potential applications include:

Bitcoin was the first cryptocurrency to achieve major success. However, it also has some real limitations.

There are constraints to the number of bitcoin transactions that can be made per second. The platform also consumes remarkable amounts of computational energy to maintain. As more transactions are added to the blockchain, the amount of energy required to maintain records will increase.

Ethereum is a competing cryptocurrency that was designed from the ground up to compensate for Bitcoins limitations. While the focus of the Bitcoin is on the currency, the focus for Ethereum is on building a sustainable blockchain platform that could eventually be used as a decentralized world computer.

Perhaps most importantly, Ethereum opened the way for.

Breakthrough #3: Smart contracts

Think about what can happen with self-executing legal agreements written as software. In this way, legal contracts could be self-monitoring, with payments made automatically when certain conditions are met. Smart contracts work even better when 5G and the emerging Internet of Things are considered.

Something fascinating is happening at the intersection of finance, law, and software coding. Imagine everything that can happen with programmable money that can follow instructions using Boolean logic (if/and/or/then). This leads us to the most recent game changer for cryptocurrency

Breakthrough #4: Decentralized finance (DeFi)

The first killer app for cryptocurrency was being able to send money around the world in seconds versus twenty-four hours for a bank wire. Fast, cheap, no middleman required. This creates a financial world with no borders or regulations.

As the ecosystem evolves, smart contracts built on Ethereum are able to perform many other functions previously controlled by banks. But unlike banks, DeFi apps are open-source. Anyone can create DeFi apps, and anyone can use them, regardless of where they live. It is now possible to exchange currencies (via the Uniswap app), borrow and lend (Compound), create futures contracts (Synthetix), run a predictions market (Augur), or raise startup funds by going public via an initial coin offering (ICO).

Some stablecoins built on the Ethereum network (such as Tether and USD Coin) live in both worldsthey have their value pegged to the U.S. dollar, but they are compatible with DeFi apps and can be transferred easily between digital wallets.

Summary

The U.S. finance industry is ripe for revolution. Fees are too high, and settlements are too slow. Roughly 80 percent of all transactions are still processed in COBOL, a programming language that goes back to the days of cardboard punch cards.

Its time for a serious update.

Is Ethereum the next big thing in digital finance? Possibly. There are other smart contract platforms worth watching, too, including Cardano, EOS, Stellar, Tezos, Hyperledger, Chainlink, and Waves. It could be a wild rideand a whole new way of doing things by 2030.

James H. Lee, CFA, CMT, CFP, APF, is the founder of StratFI, Wilmington.

Disclosure: Information contained herein is for educational purposes only and is not to be considered a recommendation to buy or sell any security or investment advice. The securities listed herein are for illustrative purposes only and are not to be considered a recommendation. The author may personally hold positions in the securities mentioned.

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Guest view: Technology, Hype, and the Future: Cryptocurrency - delawarebusinessnow.com

According to a new market report published byPersistence Market ResearchGlobal Market Study on Advanced and Predictive Analytics (APA) Software: Impelled By Deployment of Big Data Repositories,the globalAdvanced and Predictive Analytics (APA) software marketwas valued at US$ 2,422.9 Mn in 2014 and is expected to expand at a CAGR of 8.6% from 2015 to 2020. The growth of the Advanced and Predictive Analytics (APA) software market is primarily driven by the implementation of Big Data repositories, such as NewSQL, NoSQL, Hadoop databases and other platforms, to enhance the ability of computing data and business value from APA. Additionally, the shift in preference of business analysts towards becoming data scientists is also contributing in boosting the growth of the global Advanced and Predictive Analytics software market.

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Advanced and Predictive Analytics (APA) software is mainly used to discover relationships in data and make predictions that are not apparent, hidden or too complex to be extracted using query, reporting and multidimensional analysis software. The market is currently witnessing the advent of different APA software with few using its own programming language and algorithms for building models, and rest including scoring engines and model management features that can execute models built using proprietary or open source modelling languages. The future outlook of the global Advanced and Predictive Analytics (APA) software market is characterized by cloud analytics, real-time analytics, persuasion modelling and ensemble modelling.

On the basis of end-users, the Advanced and Predictive Analytics (APA) software market is segmented into banking and financial service, insurance, government, public administration and utilities, pharmaceuticals, telecom and IT, retail, transportation and logistics, healthcare, manufacturing, media and entertainment, energy (oil, gas and electricity), engineering and construction, tourism and sports. Among these, BFSI and retail are the most dominant sectors and are expected to continue the adoption of APA software during the forecast period. Additionally, with increasing data from multiple sources, other sectors, including manufacturing, education and healthcare, are also expected to witness traction in the adoption of the APA software in the near future. Rise in adoption of APA software in these sectors is attributed to the advantages it offers, such as loading and analysis of massive amounts of data in real time to accelerate ad hoc queries and reports, detecting fraud, remaining compliant and developing models to reduce cost & improve service quality.

This report also covers trends driving each market segment and offers analysis and insights on the potential of the Advanced and Predictive Analytics (APA) software market in some of the key regions, including North America, Latin America, Eastern Europe, Western Europe, Asia-Pacific (excluding Japan), Japan and the Middle East & Africa. Among these regions, the North America market was valued at US$ 1,121.3 Mn, in 2014, thereby accounting for the significant revenue share of the market, owing to the wide adoption of business intelligence solutions across diverse application segments in the region.

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The Asia Pacific (along with Japan) market was valued at US$ 313.0 Mn in 2014. The market in Asia Pacific is expected to expand at a CAGR of 8.3% during the forecast period, with countries such as India, China, Japan, South Korea, Singapore and Philippines driving the adoption of APA solutions in the region. The growth across these countries is primarily driven by several leading players, which are setting up their offices in this region with a view to expanding their operations. Also, growing Internet-based business models and application of Internet solutions in the traditional business models of enterprises is expected to create potential growth opportunities for players in the Advanced and Predictive Analytics (APA) software market during the forecast period.

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Demand for Advanced Predictive Analytics Software Market to Gain Momentum in the 2020 End-use Industry During the Forecast Period - TechnoWeekly