Categories
Game

‘Fortnite’ Chapter 3 officially debuts with a new island and revamped gameplay

It didn’t take long for Epic to confirm Fortnite Chapter 3 details. The developer has officially released a trailer that outlines what to expect both in Chapter 3 and its first season, “Flipped.” The new island is the star, with the flip from the Chapter 2 finale leading to a complete landscape overhaul that includes chaotic weather. However, the gameplay changes are arguably more important — you’ll have to rethink your tactics.

The sliding and swinging mechanics should help you move (and dodge) faster than before. Camps help your squad heal and store items that persist between matches. You can also earn XP beyond battle royale, and hold on to a Victory Crown if you keep winning. Epic is clearly hoping to both foster a non-combat metaverse and keep its top-tier players coming back.

And yes, there are new characters. Spider-Man is well-suited to the new swinging mechanic, but you can also play as Dwayne “The Rock” Johnson’s Fortnite character The Foundation, or Gears of War‘s Marcus and Kait. Think of them as the poster children for Chapter 3. They may help draw you in, but it’s the fresh gameplay that might keep you playing in the long run.

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Game

Suicide Squad: Kill The Justice League Gameplay Debuts

Warner Bros. and Rocksteady Studios presented their latest trailer for the Suicide Squad: Kill The Justice League at The Game Awards on Thursday. The trailer featured a lengthy gameplay preview and a confirmed release date of sometime in 2022. Suicide Squad is coming to PC, PlayStation 5, and Xbox Series X/S. There was no mention of it coming to the PlayStation 4 and Xbox One.

Rocksteady revealed glimpses of gameplay through past trailers and social media snippets before, but nothing as in-depth as the gameplay in The Game Awards trailer. Developers announced they would be appearing at The Game Awards with a gameplay preview on social media before the show.

In the trailer, Suicide Squad members Harley Quinn, King Shark, Captain Boomerang, and Deadshot ripped apart the city with their powers and abilities in what seemed like a citywide battle. Each member showcased their own unique fighting style based on their strengths —  fists in the case of King Shark and blasters for Deadshot. The team faced a corrupted version of the Flash and other demonic creatures running amok in the city. Though they weren’t featured, other members of the Justice League will likely appear in the game, too.

Suicide Squad is only one of the comic book hero video games announced in recent years. Other comic book-related titles include Marvel’s Guardians of the Galaxy, Marvel’s Avengers, and Marvel’s Spider-Man: Miles Morales.

Rocksteady Games originally announced Suicide Squad in 2020 at the DC FanDome. For reference, Rocksteady Studios already produced critically acclaimed DC-related work for the Batman Arkham series. So, at the very least, the game has some developers who are familiar with DC behind the wheel.

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Game

‘Battlefield 2042’ won’t have voice chat when it debuts on November 19th

When  comes out in about a week on , it won’t ship with built-in voice chat. Series developer DICE told the feature won’t be available until sometime after launch. The studio didn’t provide a reason for the decision. Whatever the case, the absence of voice chat will likely be keenly felt by Battlefield fans, especially on PC, Xbox Series X and S, and PlayStation 5 where matches will include as many as 128 players.

For what it’s worth, you can still use Discord or the party chat feature on your console to communicate with friends, but that won’t help you when you’re trying to play with strangers. In those instances, you’ll need to rely on the ping system, which is apparently on the cumbersome side. According to Polygon, you have to navigate through multiple menus before you can get to the right ping. All told, it sounds like Battlefield’s already chaotic matches will be a tad more unpredictable in the first few weeks that 2042 is available.

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AI

Byju’s debuts innovation hub for edtech ventures

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India’s Byju’s has created a new innovation hub, dubbed Byju’s lab, where it hopes to bringing together AI and machine-learning experts with educational technology researchers to create new edtech solutions.

The Bengaluru, India-based company has grown to more than 100 million students (and 6.5 million paid subscriptions) with its kids educational games platform, and it has been on a buying spree as it expands well beyond India’s borders.

Byjus’s bought U.S.-based AR game maker Osmo for $120 million in 2019. It also raised $150 million (following a $540 million round) for its global expansion that year. This year, Byju’s launched its Disney-based learning app for U.S. children, and it bought the kids online reading platform Epic for $500 million. And it bought Tynker’s for an estimated $200 million. The acquisitions map back to Byju’s goal of investing $1 billion in the U.S. edtech market over the next three years.

The new hub will redefine the role of tech in learning and transform powerful ideas into solutions. It will hire AI and ML specialists in the United Kingdom, the U.S., and India.

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With a vision to propel and shape the future of education, the new venture will incubate new ideas, provide cutting-edge technologies and deliver breakthrough solutions across Byju’s ecosystem of learning products.

The company said that technology in education is not just about automation, but also about harnessing it in the best way possible to empower students into becoming lifelong learners. It believes that by innovating for the future we will sustain the present, and Byju’s Lab stems out of this philosophy to aid in redefining the role of technology in learning and transforming powerful ideas into solutions.

Byju’s Lab is yet another step in the company’s efforts to continue innovating with the aim to transform learning experiences for children around the world. It is doing so by leveraging cutting edge technologies such as augmented reality, artificial intelligence (AI), computer vision capabilities, gamification and more.

Dev Roy, chief innovation and learning officer at Byju’s said in a statement, “The role of online learning is not just to replicate offline classes in digital space but to make it more interactive, engaging, and personalized. By combining the ability of computing, technology, and data, we at Byju’s Lab, want to explore the power of information and technology to create a more personalized, enhanced, and democratized learning. As a global company, we are looking to harness a global talent pool to build innovative tools and leverage new technologies to positively impact the learning experiences of children across the world. As we continue to grow and experiment, we will operate at the intersection of business and technology to make innovation real and relevant for our end customers. We are looking at strengthening our team and look forward to working with bright and curious minds to transform the way children learn.”

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AI

Nvidia debuts ReOpt to optimize supply chain routing with AI

During a keynote address at its fall 2021 GPU Technology Conference (GTC), Nvidia debuted ReOpt, a software package that combines local search heuristics algorithms and “metaheuristics” to optimize vehicle route planning and distribution. According to the company, ReOpt can improve route planning, warehouse picking, fleet management, and more in logistics to control delivery costs from factories to stores and homes.

Companies are increasingly facing supply chain challenges caused — or exacerbated — by the pandemic. A U.S. Census Bureau survey f0und that 38.8% of U.S. small businesses were experiencing domestic supplier delays by the middle of July 2021. Late deliveries can seriously impact customer loyalty, with one survey finding that 80% of shoppers would cut ties with brands if they experienced stock shortages.

“At a time when the global supply chain faces massive disruption, ReOpt provides the AI software required for everything from vehicle routing for last-mile delivery to efficiently picking and packing of warehoused goods bound for homes and offices,” Nvidia software engineering manager Alex Fender said in a blog post. “ReOpt delivers new tools for dynamic logistics and supply chain management to a wide range of industries, including transportation, warehousing, manufacturing, retail, and quick-service restaurants.”

AI-powered logistics

Delivering goods directly to a customer’s door, called last-mile delivery, was costly even before the pandemic disrupted the global supply chain network. Over half of all air, express, rail, maritime, and truck transport shipping costs result from last-mile deliveries, impacting profitability, according to ABI Research. Onfleet estimates that companies typically eat about 25% of that cost themselves — a number that continues to increase as bottlenecks worsen.

ReOpt, which is now available in early access, taps algorithms to provide customers with road condition, traffic, and route metrics to reduce miles, fuel cost, carbon emissions, and idle time. The service models the movements of vehicles that have finite capacities and different costs, factoring in items like fresh produce that must be carried by refrigerated trucks. ReOpt also allows customers to create automated routines that dynamically route robots for truck loading as new orders arrive. And it can take into account the number of pilots, drivers, and workers available to operate vehicles on a given day, folding in maintenance costs.

“GPUs offer the computational power needed to fuel the most ambitious heuristics while supporting the most challenging constraints. ReOpt takes advantage of Nvidia’s massively parallel architecture to generate thousands of solution candidates and refine them to select only the best one at the end,” Fender continued. “As a result, ReOpt can scale to the largest problems in seconds with world-class accuracy.”

A growing number of companies are developing AI services to optimize components of the supply chain. DispatchTrack provides AI-powered route optimization, reservations, billing and settlement, and omnichannel order tracking tools. Locus is also developing a platform for logistics and “enterprise-scale” supply chain automation. Others in the global logistics market — which is expected to be grow to $12.68 billion in value by 2023, according to Research and Markets — are Convoy, Optimal Dynamics, KeepTruckin, and Next Trucking, which have collectively raised hundreds of millions in venture capital.

Tech giants have entered the fray, too — most recently Microsoft with its Supply Chain Insights product. Uber’s eponymous Uber Freight connects carriers and drivers with companies that need to move cargo. As for Google’s Supply Chain Twin, which became generally available in September, it organizes data in Google Cloud to expose a more complete view of suppliers, inventories, and events like weather.

While only 12% of manufacturing and transportation organizations are currently using AI in their supply chain operations, 60% expect to be doing so within the next four years, according to MHI. This dovetails with a recent PwC report, which found that 48% of companies are ramping up investments for simulation modeling and supply chain resilience.

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AI

Google debuts new data-powered cloud analytics products

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Today during its Google Cloud Next 2021 conference, Google unveiled a range of data-focused products including Intelligent Product Essentials and enhancements to Vertex AI, BigQuery, Contact Center AI (CCAI), and DocAI. The new analytics and industry solutions are designed to simplify how organizations derive value from data, Google says — whether they’re developing a new product or enhancing existing ones.

AI adoption and analytics are rising during the pandemic, with 20% of companies claiming they’ve boosted their usage of business analytics compared with the global average. But while 97% of execs say data science is “crucial” to maintaining profitability, several major challenges stand in the way. A Dremio report found that only 22% of data leaders have realized a return on investment in data management in the past two years.

“The focus on intelligent products that Google Cloud is [launching] provides a digital option for [customers],” IDC group VP Kevin Prouty said in a statement. “IDC sees faster and more effective decision-making as the fundamental reason for the drive to digitize products and processes. It’s how you can make faster and more effective decisions to meet heightened customer expectations, generate faster cash flow, and better revenue realization.”

Intelligent Product Essentials

Intelligent Product Essentials aims to assist manufacturers in developing hardware products. With it, they’re able to deliver AI-enabled devices that can update over-the-air and provide insights using analytics in the cloud, according to Google.

Intelligent Product Essentials can be used to create personalized customer experiences — for example, a chatbot that contextualizes responses based on product status and customer profiles. The service can also deploy updates to products in the field and gather performance insights, as well as evolve capabilities over time with monetization opportunities.

Intelligent Product Essentials predicts parts and service issues, detecting operating thresholds, anomalies, and failures so it can proactively recommend service using AI. Customers can leverage the offering to connect and ingest raw or time-series product telemetry from various device platforms to support over-the-air updates. In addition, Intelligent Product Essentials lets developers build companion apps that work on smartphones, tablets, and computers using a prebuilt API that incorporates product and security, device registration, and app behavior analytics.

“Intelligent Product Essentials [can] manage, update and analyze fleets of connected products via APIs,” Google wrote in a blog post. “[Companies can] create new features or capabilities for [their] products using AI and machine learning … [and] integrate data sources such as enterprise asset management, enterprise resource planning, customer relationship management, systems and others.”

Vertex AI, BigQuery, and Spark

Google introduced Vertex AI, a managed AI platform, in May at Google I/O 2021. Today, it’s expanding the service with Vertex AI Workbench, a user experience to build and deploy AI models faster, accelerating time-to-value for data scientists and their organizations.

Data scientists spend the bulk of their time cleaning and organizing data, according to a 2016 survey conducted by CrowdFlower. In a recent Alation report, a majority of respondents (87%) pegged data quality issues as the reason their organizations failed to implement AI. That’s perhaps why firms like Markets and Markets anticipate that the data prep industry, which includes companies that offer data cataloging and curation tools, will be worth upwards of $3.9 billion by the end of 2021.

Whereas Vertex AI is designed to help companies accelerate the deployment and maintenance of AI models, Workbench focuses specifically on integrating data engineering capabilities into the data science environment. Workbench incorporates Dataproc, BigQuery, Dataplex, Looker, and other Google Cloud services, facilitating the ingestion and analysis of data from a single interface.

“Delivered through managed notebooks, these capabilities help data scientists rapidly build workflows and perform the coordination, transformations, security, and machine learning operations, all within Vertex AI,” Google wrote.

On the BigQuery side, Google is making generally available BigQuery Omni, which allows businesses to analyze data across Google Cloud, Amazon Web Services, and Microsoft Azure. The managed, cross-cloud analytics solution helps to answer questions and share results from a single pane of glass across datasets, complementing Google’s Dataplex service (which will be generally available this quarter) to make data accessible to more analytics tools.

Google also today announced a preview of Spark on Google Cloud, which the company claims is the world’s first autoscaling and serverless Spark service for Google Cloud. It allows data engineers, data scientists, and data analysts to use Spark from their preferred interfaces, writing apps and pipelines that autoscale without manual infrastructure provisioning or tuning.

Looker and Spanner

To complement the rest of its data-focused offerings, Google is continuing to make Cloud Spanner, its fully managed, relational database, available to customers via a PostgreSQL interface (in preview). The interface supports several popular PostgreSQL data types and SQL features, allowing schemas and queries built against the PostgreSQL interface to be ported to another Postgres environment.

Beyond this, Google debuted new integrations with Looker that it says will allow customers to “operationalize analytics” and more effectively scale deployments. Tableau customers and Connected Sheets users will soon be able to leverage Looker’s semantic model, with the Connect Sheets integration launching in preview by the end of the year. Looker’s new solution for CCAI will help to contextualize support calls coming in to enterprise call centers. And the forthcoming Looker Block for Healthcare NLP API, which is compatible with the Fast Healthcare Interoperability Resources (FHIR), will provide health care providers, payers, and pharma companies access to insights from unstructured medical text from clinical sources.

Google Earth Engine

Touching on the geospatial, Google unveiled Google Earth Engine on Google Cloud, which makes Google Earth Engine’s catalog of over 50 petabytes of satellite imagery and geospatial datasets available for analysis. Google says that Google Cloud customers will be able to integrate Earth Engine with BigQuery, Google Maps Platform, and Google Cloud’s AI technologies, giving data teams “a way to better understand how the world is changing and what actions they can take” — from saving energy costs to understanding business risks and serving customer needs.

Investments in “green” practices aren’t just beneficial for the environment — they make business sense. According to a 2017 study on corporate social responsibility, 87% of consumers have a more positive image of companies that support social or environmental issues. Moreover, 87% say they’d buy a product with a social and environmental benefit, and 88% would more loyal to a company that supports those efforts.

“For over a decade, Earth Engine has supported the work of researchers and nongovernmental organizations from around the world, and this new integration brings the best of Google and Google Cloud together to empower enterprises to create a sustainable future for our planet and for your business,” Google wrote.

CCAI and DocAI

Google Cloud’s CCAI, which offers AI-powered virtual agents and other features, entered general availability in 2019, while the company’s AI-powered document processing service DocAI rolled out in April. Now, the two services are each gaining new features in CCAI Insights and Contract DocAI. CCAI Insights provides out-of-the-box and custom data modeling techniques, and Contract DocAI — now in preview — brings features purpose-built for contract lifecycles and processing.

Over the past several years, businesses have increasingly turned to cloud-based contact centers to address budding customer service challenges. The pandemic accelerated that move — service conveniences were put in place out of necessity, which gave customers more options for interacting with companies. For example, 78% of contact centers in the U.S. now intend to deploy AI in the next 3 years, according to Canam Research. And research from The Harris Poll indicates that 46% of customer interactions are already automated, with the number expected to reach 59% by 2023.

CCAI Insights uses AI to mine raw contact center interaction data for actionable information, regardless of whether that data originated with a virtual or human agent. It provides out-of-the-box analytics on customer conversations including Smart Highlighters, which automatically highlights important conversation moments such as when an agent authenticates or a customer confirms that their issue has been resolved. Meanwhile, integration with Google’s Cloud Natural Language Processing (NLP) identifies positive or negative sentiment and labels various entities within conversations by types, including date, person, contact information, organization, location, events, products, and media.

CCAI Insights — which can hand off calls and chats handled by Dialogflow and Agent Assist — also categorizes conversations with custom highlighters, which let customers defines rules, keywords, and natural language training phrases. Topic modeling — another capability — leverages NLP technologies so teams can create an AI model of their data to define the taxonomy of conversation drivers.

As for Contract DocAI, it taps NLP, knowledge graph technology, and optical character recognition to parse contracts for key terms like those involving start and end dates, renewal conditions, parties involved, contract type, venue, or service level agreements. It automatically discerns important terms and the relationships among them, potentially leading to faster and less expensive contract processing, Google claims.

“All of these new additions will help transform businesses by making the power of AI more accessible and more focused on achieving business outcomes,” Google wrote. “[The] announcements build on the momentum we’ve been seeing with our AI solutions in delivering business value to our customers.”

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Game

Bionicle Fan Game Debuts Gorgeous Environmental Trailer

A team of Bionicle fans isn’t willing to let the strange franchise disappear just yet. With Lego’s blessing, developer Team Kanohi is putting together a full-on 3D adventure through the strange world of the Toa titled Bionicle: Masks of Power. A new trailer for the fan project just debuted, presenting an impressive look at the Bionicle universe and the Lego creatures that live in it.

Bionicle is one of the Lego group’s many franchises, but it may just be its most niche. It started in 2000 giving kids strange, masked characters to assemble. However, Bionicle has gained a cult following over the years thanks to its extensive lore. The entire franchise had an underlying story told through webcomics, games, books, and eventually direct-to-DVD movies. The original run of Bionicle ended in 2010, with a revival lasting only one year, from 2015 to 2016.

Team Kanohi’s revival of the Bionicle IP already looks impressive. The project has been in the works for five years, though we’d only seen a pair of short teasers in that time. An environmental trailer for Masks of Power offers the first real tour of the game’s world, which has been created using Unreal Engine 4. The trailer goes across multiple environments, from snowy tundra to volcanic wastelands littered with lakes of lava.

Of course, Bionicle creatures show up in the trailer as well, appearing highly detailed and even faithful to the original builds.

While the game doesn’t currently have a release date, its website offers some details on what players can eventually expect. Bionicle: Masks of Power is going to be an open-world game where players will “face challenging puzzles, fearsome beasts, and deadly hazards as you endeavor to find all 12 masks.”

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Tech News

Sony Airpeak S1 drone debuts to take Alpha cameras to new heights

Drones for pros and consumers are nothing new and neither are drones with cameras covering a wide range of qualities. Most of these drones come with their own cameras, however, and few actually let you use whatever professional camera you may already own. That’s what makes Sony’s first foray into the world of drone photography interesting in that it is designed to be used with a different camera, specifically Sony’s own interchangeable-lens Alpha cameras. In fact, the Sony Airpeak S1 drone doesn’t come with a camera or even a gimbal of its own.

Announced late last year and teased at this year’s virtual CES 2021, the Airpeak S1 is marketed at professional photographers and cinematographers but doesn’t actually include that critical part of the equation. While most drone makers would highlight that aspect of their new UAVs, Sony is already confident it has the camera part down pat. What Sony is boasting about with its first-ever pro drone is, instead, its flying capabilities.

Unsurprisingly, Sony talks a lot about the proprietary motors and technologies that enable the drone to fly stably at max speeds of 55mph (90km/h). While it might not have a camera for recording video, it does have imaging sensors facing all directions, including downward, to see its surroundings and fly reliably.

The Airpeak S1 drone is designed to target professionals and it includes features that enable that use case. That includes a dual operation mode that lets one person operate the drone while another operates the gimbal and camera, both of them seeing the same video feed. It also has an “Airpeak Base” web application that lets users manage flight plans and flight logs in addition to the Airpeak Flight app for iOS and iPadOS.

Unsurprisingly, the Sony Airpeak S1 also comes with a professional price of $9,000. That price doesn’t yet include even the special gimbal that is necessary to attach Sony Alpha cameras, like the A7S, A7R, and FX3 series. That will be a separate purchase and neither the drone nor the gimbal has specific launch dates just yet.

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AI

Baidu debuts updated AI framework and R&D initiative

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At Wave Summit, Baidu’s bi-annual deep learning conference, the company announced version 2.1 of PaddlePaddle, its framework for AI and machine learning model development. Among the highlights are a large-scale graph query engine; four pretrained models; and PaddleFlow, a cloud-based suite of machine learning developer tools that include APIs and a software development kit (SDK). Baidu also unveiled what it’s calling the Age of Discovery, a 1.5 billion RMB (~$235 million) grant program that will invest over the next three years in AI education, research, and entrepreneurship.

At Wave Summit, Baidu CTO Haifeng Wang outlined the top AI trends from the company’s perspective. Deep learning with knowledge graphs has significantly improved the performance and interpretability of models, he said, while multimodal semantic understanding across language, speech, and vision has become achievable through graphs and language semantics. Moreover, Wang noted, deep learning platforms are coordinating closely with hardware and software to meet various development needs, including computing power, power consumption, and latency.

To this end, PaddlePaddle 2.1 introduces optimization of automatic mixed precision, which can speed up the training of models — including Google’s BERT — by up to 3 times. New APIs reduce memory usage and further improve training speeds, as well as adding support for data preprocessing, GPU-based computation, mixed-precision training, and model sharing.

Also in tow with PaddlePaddle 2.1 are four new language models built from Baidu’s ERNIE. ERNIE, which Baidu developed and open-sourced in 2019, learns pretrained natural language tasks through multitask learning, where multiple learning tasks are solved at the same time by exploiting commonalities and differences between them. Beyond this, PaddlePaddle 2.1 brings an optimized pruning compression technology called PaddleSlim, as well as LiteKit, a toolkit for mobile developers that aims to reduce the development costs of edge AI.

PaddlePaddle Enterprise and Age of Discovery

PaddlePaddle Enterprise, Baidu’s business-oriented set of machine learning tools, gained a new service this month in PaddleFlow. PaddleFlow is a cloud platform that provides capabilities for developers to build AI systems, including resources management and scheduling, task execution, and service deployment via developer APIs, a command-line client, and an SDK.

In related news, Baidu says that as a part of its new Age of Discovery initiative, the company will invest RMB 500 million ($78 million) in capital and resources to support 500 academic institutions and train 5,000 AI tutors and 500,000 students with AI expertise by 2024. Baidu also plans to pour RMB 1 billion ($156 million) into 100,000 businesses for “intelligent transformation” and AI talent training.

Laments over the AI talent shortage have also become a familiar enterprise refrain. O’Reilly’s 2021 AI Adoption in the Enterprise paper found that a lack of skilled people and difficulty hiring topped the list of challenges in AI, with 19% of respondents citing this as a “significant” barrier. In 2018, Element AI estimated that of the 22,000 Ph.D.-educated researchers working on AI development and research globally, only 25% are “well-versed enough in the technology to work with teams to take it from research to application.”

“PaddlePaddle researchers and developers will collaborate with the open source community to build a deep learning open source ecosystem and break the boundaries of AI technology,” Baidu said in a press release. “With the permeation of AI across various industries, it is critical for platforms to keep lowering their threshold to accelerate intelligent transformation.”

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AI

Appian debuts new low-code features for enterprise

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Software company Appian this morning unveiled the latest version of its low-code automation platform. The new release introduces AI-driven intelligent document processing (IDP) and developer collaboration features, as well as enhanced DevSecOps capabilities and what Appian calls “low-code data,” a code-free approach to unifying enterprise data.

Research firm Gartner estimates the market for hyperautomation-enabling technologies will reach $596 billion in 2022, up nearly 24% from the $481.6 billion in 2020. As organizations look for ways to accelerate the digitization and structuring of data and content, technologies like document ingestion and natural language processing will remain in high demand.

Appian

Low-code data headlines the enhancements launched today. Using it, Appian customers can source data without needing to migrate and visually combine, extend, and model relationships between data. This lets them automatically optimize datasets for performance without coding or database programming.

“Appian strips away the complexities of working with the most advanced automation technologies so we can focus on making our member experience the best it can be,” Matt Richard, CIO at Laborers International Union of North America (LiUNA) and an Appian customer, said in a press release. “We were able to build our first Appian robotic process automation process in just four days, integrated with our people processes and Appian AI. Simplifying data design is going to have a huge impact for us so I am looking forward to the new release with low-code data.”

Document processing and app development

On the document processing side, Appian says its updated platform is capable of straight-through processing of large volumes of unstructured data. IDP features optical character recognition to extract data from documents without third-party software or services, and it ships alongside new low-code robotic process automation Windows actions and libraries of actions that can be downloaded directly from Appian’s marketplace.

Studies like IBM’s Global AI Adoption Index survey support the notion that enterprise deployment of automation is increasing. Adoption is being driven by both pressures and opportunities, from the pandemic to technological advances that make AI more accessible. Indeed, a third of companies told IBM that they plan to invest in automation skills and solutions over the next 12 months.

The new Appian platform release also lets organizations build and change apps and automations faster than before. Collaboration capabilities simplify the co-creation of apps while enhanced design guidance optimizes app performance, security, and testing. Meanwhile, new DevSecOps tools streamline the movement of software packages between development, test, and production environments.

Appian says the latest version of its platform will be generally available in June 2021.

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