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General Mills, Inc. manufactures and markets branded consumer foods worldwide. The company operates in five segments: North America Retail; Convenience Stores & Foodservice; Europe & Australia; Asia & Latin America; and Pet. It offers ready-to-eat cereals, refrigerated yogurt, soup, meal kits, refrigerated and frozen dough products, dessert and baking mixes, frozen pizza and pizza snacks, snack bars, fruit snacks, nutrition bars, and savory snacks, as well as organic products, including refrigerated yogurt, frozen and shelf-stable vegetables, meal kits, salty snacks, ready-to-eat cereal, and grain snacks. It also supplies branded and unbranded food products to the North American foodservice and commercial baking industries; and manufactures and markets pet food products, including dog and cat food. The company markets its products under the Annie's, Betty Crocker, Bisquick, Blue Buffalo, BLUE Basics, BLUE Freedom, BLUE Wilderness, Bugles, Cascadian Farm, Cheerios, Chex, Cinnamon Toast Crunch, Cocoa Puffs, Cookie Crisp, EPIC, Fiber One, Food Should Taste Good, Fruit by the Foot, Fruit Gushers, Fruit Roll-Ups, Gardetto's, Go-Gurt, Gold Medal, Golden Grahams, HÃ¤agen-Dazs, Helpers, Jus-Rol, Kitano, Kix, LÃ¤rabar, Latina, LibertÃ©, Lucky Charms, Muir Glen, Nature Valley, Oatmeal Crisp, Old El Paso, Oui, Pillsbury, Progresso, Raisin Nut Bran, Total, Totino's, Trix, Wanchai Ferry, Wheaties, Yoki, and Yoplait trademarks. General Mills, Inc. sells its products directly, as well as through broker and distribution arrangements to grocery stores, mass merchandisers, membership stores, natural food chains, e-commerce retailers, commercial and noncommercial foodservice distributors and operators, restaurants, convenience stores, and pet specialty stores, as well as drug, dollar, and discount chains. It operates 500 leased and 358 franchise branded ice cream parlors. General Mills, Inc. was founded in 1866 and is headquartered in Minneapolis, Minnesota.

General Mills

generalmills

General Mills Inc (GIS) is near the middle in its sector according to InvestorsObserver. GIS gets an overall rating of 23. That means it scores higher than 23% of stocks. General Mi

Will General Mills Inc (GIS) Stay at the Bottom of the Consumer Defensive Sector?

80% of Americans tested were found to have been exposed to the chemical chlormequat, which has been linked to issues with puberty and reproduction, a study claims.

Chemical That May Cause Infertility Found in Cheerios, Quaker Oats

https://www.chexmix.com/chexquest/ Once thought to be impossible is now possible. Companies can create their own video games for advertising purposes. My game studio specializes in creating advergames for ad agencies and brand managers. Often, our games are rated quite highly as consumers love the experience. Sometimes they even top the mobile charts. I’m here to answer the questions I receive most often from ad agencies looking to learn about the space. Question: What Are Advergames? An advergame is a type of video game that is designed to promote a product, service, or brand. These games are often created by advertising agencies and are used to increase brand awareness and engagement. Advergames are designed to be fun and engaging. They can take many different forms, including mobile games, browser games, and even console games. They are typically distributed online, through social media, or on a brand’s website, and they can be played for free. Another key characteristic of advergames is that they don’t contain programmatic ads or other forms of monetization such as in-app purchases. Question: What Are The Advantages of Advergames? One of the key advantages of advergames is that they allow brands to connect with consumers in a more interactive and engaging way. Unlike traditional forms of advertising, which can be passive and easily ignored, advergames provide an immersive experience that can hold the player’s attention for longer periods of time. This makes advergames an effective way to increase brand affinity, product recall, and intent to buy. of a snack company. In one landmark case study, Frameplay.gg leveraged game marketing to increase brand affinity by 46% and intent to purchase by 26% In addition to promoting a brand, advergames can also be used to educate consumers about a product or service. For example, a game could be designed to teach players about the benefits of a new car or to explain the features of a financial service in an engaging and interactive way. Advergames are typically described as “mid-funnel” marketing tools. However, they can aid with lower-funnel objectives such as driving site traffic and even sales. Quite often, advergames will include an which will offer players in-game and physical rewards for following a link to the brand’s site. Studies suggest that these incentivized CTAs can have ! incentivized call-to-action click-through rates as high as 43% Question: What Are Some Examples of Advergames? “ ,” an advergame created by Chipotle in 2016. The game challenged players to collect ingredients and build burritos as they race through different levels. The game helped to increase brand awareness and engagement for Chipotle, and it also encouraged players to visit Chipotle restaurants to redeem rewards and prizes. Chipotle Race to Rewards “ ” an advergame created by PepsiCo in 1999. The game featured a humanoid character, Pepsi-Man, who ran through different levels and collected Pepsi cans while avoiding obstacles and enemies. The game helped to increase brand awareness and engagement for Pepsi and its products. Pepsi-Man, “ ,” an advergame created by General Mills in 1996 & revived in 2020. The game featured characters from the popular Chex cereal brand, who were tasked with exploring different levels and defeating enemies in order to save the galaxy. The game helped to increase brand awareness and engagement for the Chex brand and to promote the benefits of eating whole-grain cereal. Chex Quest “ ” an advergame for Mortgage Hero in 2022, is designed to help first-time homebuyers learn about the complexities of obtaining a mortgage. The game provided a brand lift to Mortgage Hero and served as a lead generation. 82% of survey respondents were better able to describe the Mortgage Hero product offering after playing their advergame. Mortgage Race, Question: What Are the Challenges with Producing a Successful Advergame? There are a few things to consider before creating an advergame: If the game isn’t fun, it’s not going to be successful. Creating a game that is both fun and engaging, while also effectively promoting a brand or product, can be difficult; as advergames need to balance entertainment value with promotional objectives. Be Genuine, Novel, & Fun — Develop a game that is appropriate for the target audience. Advergames need to be tailored to the interests and demographics of the target audience. Remember, ! Target an Audience — 80% of all smartphones have a game installed on them, which means that “gamers” are not a niche Mobile gamers consist of all ages and genders, but the of the game can affect the audience of who’s willing to play. For instance, . genre first-person shooter games tend to be dominated by younger men while match-3 games are beloved by older women Advergames need to be evaluated in terms of their effectiveness in promoting a brand or product and in terms of their impact on consumer engagement, brand awareness, and sales. This can require sophisticated tracking and analytics tools. Gather Data — Just because you built an advergame doesn’t mean that gamers will naturally find it. Ensure the game has a so the advergame winds up on the top iOS/Android/Steam and . My recommendation is to leverage influencer marketing, however, programmatic marketing on social media or fantasy IP will also work! Market the Advergame — marketing catalyst garners organic growth — Advergames tend to have competitive eCPM pricing to other forms of marketing. However, they tend to require more upfront costs to build the game and market the game. They also tend to have slightly longer activation time than other channels, though game studios that specialize in advergames have experience shipping quarterly. Think About Upfront Cost and Activation Time Question: How Does Marketing via an Advergame Compare to Traditional Game Marketing Methods Such as Programmatic, Metaverse, and Sponsoring an eSport team? Creating an advergame has several advantages over other forms of game marketing. First, creating an advergame allows a brand to have complete control over the content and messaging of the game. This ensures that the game is and consistent with the brand’s image and values. brand-safe In contrast, programmatic advertising and sponsored eSports teams do not provide the same level of control, and there is a risk that the brand’s message could be diluted by other content. Second, advergames are inherently engaging, as they provide a fun and interactive experience for players. This can help to increase consumer engagement with the brand and its products or services, and it can also foster positive associations and longer-term loyalty. In contrast, programmatic advertising and sponsored esports content can be less engaging, and . they may not provide the same level of interaction or immersion Third, advergames can be used to educate consumers about a brand or product, by incorporating informative and instructional elements into the game. This can help to increase consumer awareness and understanding of the brand and its offerings. Lastly, advergames come with great data. Because the brand owns the game, they’re able to measure everything they would like. Impressions, click-through rates, and what products received the most in-game attention. really Conversely, other gaming activations can be more limited in their data gathering. For instance, McKinsey found that eSport activations often only reached a fraction of the audience that was advertised by the vendor. Question: Why Are Mobile Advergames Set to Take Off? Advergames are taking off on mobile due to the recent advancements in , which have significantly reduced the cost and effort required to develop and deploy these games. low-code technology Low code technology allows for the creation of complex, interactive games with minimal coding and development resources, which has made it much more accessible and affordable for brands to create and distribute advergames. In addition to the cost savings provided by low code technology, mobile advergames are also benefiting from the tremendous traffic that the Apple App Store and Google Play Store receive on a daily basis. These app stores are the primary distribution channels for mobile games, and they provide a massive audience of potential players for advergames. The sheer volume of users and downloads on these app stores makes them an attractive platform for advergames, as they can reach a large and engaged audience with minimal effort and cost. Furthermore, advergames are well-suited to the mobile platform, as they can provide a fun and engaging experience for users while they are on the go. , and advergames can capitalize on this trend. Mobile devices are increasingly becoming the primary means of playing games I do expect advergames to completely dominate the iOS/Android top 100 free games list in the next decade as they provide a better experience to the consumer than freemium games currently on the market. are getting sick of programmatic ads in games. They’re looking for an experience that’s more genuine, and ad agencies need to activate campaigns where their consumers are. The population of 3 billion active mobile gamers Looking to create your own advergame? Get in touch! Feature image source Also published here

Are Advergames the Future of Digital Marketing?

¿Son los advergames el futuro del marketing digital?

Les Advergames sont-ils l'avenir du marketing numérique ?

क्या एडवरगेम्स डिजिटल मार्केटिंग का भविष्य है?

Advergames はデジタル マーケティングの未来ですか?

Advergames são o futuro do marketing digital?

Trò chơi quảng cáo có phải là tương lai của tiếp thị kỹ thuật số không?

Advergames 是数字营销的未来吗？

Whether you are a company, a job seeker, or an influencer, building a brand is crucial to your success. And just like corporate brands, influencers and creators can use the same best practices to develop their brands. However, influencers are unique in that they are both a brand and a media channel themselves. Traditional brands can work with influencers to promote their products, but influencers must also maintain their image — and the independent voice, unique perspective, or point of view — that built up your following and engaged their audience in the first place. This means that creators or influencers carry a different voice that is inherently different from corporate brands. They can use that voice to create content that remains authentic to the creator, lending a powerful third-party endorsement of a type traditional, "corporate" brands cannot do themselves (for obvious reasons). Creating a "personal brand" as an influencer is vital to your longevity. Sharing high-quality, original content your audience finds engaging is the most powerful tool in the brand building shed. Be everywhere One of the first things an influencer must do is establish reach and make their brand known. Creating a comprehensive online presence is paramount in the digital era—in other words, be everywhere. Like building a personal website or LinkedIn profile when applying to jobs, joining every social media platform using similar handles increases visibility and findability online. Even if the influencer only chooses to focus on one or two platforms, having the other profiles: 1. Protects them and their brand from being impersonated or abused; 2. Allows them to experience various platforms and narrow down which ones are the best fit for the creator and the content they want to create; 3. If they want to growーeasily allows them to expand into more platforms since they already have accounts set up; 4. Casts a broader net online to attract more viewers and followers. Creators can even use these profiles to direct viewer traffic and point them in the direction of their leading platforms, whether that is on social media or even to their website. While being everywhere increases the chance of gaining an audience and following as an influencer, it also increases the chances of brands discovering them for lucrative collaborations. Establishing an online presence builds credibility and trustworthiness, making it easier for potential brands to reach out and collaborate. Choosing a niche As a creator, positioning and targeting are also crucial to getting noticed. For a corporate brand, positioning often depends on the product or service and how it compares or differs from competitive offerings. A creator's positioning depends more on the expertise or content they create for a personal brand. Building a personal brand also takes discipline. Tom Fishburne, a former marketing executive at General Mills who left the corporate world to pursue his passion for creating cartoons, understands the raw, under-appreciated power of a niche. In his case, Tom draws insightful cartoons that just about any marketer can relate to -- and get a laugh out of. Usually, these cartoons address a topic of discussion in the space, and he accompanies his cartoons with compelling blog posts that add context and insight to the issue at hand. : As Tom puts it "Your target market is not the same as anyone who could conceivably buy your product. A target market is deliberately exclusive. That niche focus is what gives it teeth. It is what compels consumers to identify with your brand. It is what gives you the insight to speak to them so clearly." Niches are critical because they differentiate creators from one another, especially in a saturated market like social media influencers. They provide a unique identity that is easy for brands to pinpoint and makes choosing influencers much easier. Niches can also establish legitimacy and expertise. Creators can "own" a space by becoming category leaders in their place, making them stand-out choices for brands to work with. Simply put, having a niche establishes boundaries of what an influencer's brand can and can't be; subsequently, what an influencer can and can't promote. Without context, it's jarring to hear a financial creator extol the virtues of Hot Pockets. As an influencer, their niche makes them the expert; speaking on that niche gives them an authentic connection to their followers and appropriate promotion for a brand. Niches contribute to an influencer's brand's overall look and feel, making it easier for viewers to understand what kinds of content to expect. However, a niche shouldn't pigeonhole a creator into one piece or one form of content. Instead, it should focus on retaining a group of viewers dedicated to following that influencer's content. Creators should be free to explore whatever topics and themes they want, so long as it is in their voice. One of the best niches to occupy is simply a creator's personality. A creator who has a following solely on their personality will speak on any topic or theme with complete authenticity. Because each character is unique, the creator has an irreplicable position they can leverage forever. Although there is technically no limit to what niches content creators want to occupy, there are some rigid boundaries as to what types of content are allowed on each platform. One of the most overlooked steps when signing up for a platform is reading the terms of service. These documents outline what types of content are banned or restricted on the platform. As a content creator, it is essential to be aware of these categories and avoid choosing a niche, as the platform can stop a creator's journey before it even starts. Additionally, when it comes to promotions, platforms become even more restrictive of what kinds of products & services can be advertised. Some of the most common restricted categories include financial products, gambling, health & wellness products such as weight loss products or vitamins, and relationship or dating products. When unverified, these categories can carry significant risk to consumers and thus usually have to be directly approved by the platform themselves. On the other hand, a niche is not an invitation to sell out either: creators who do not enjoy the content they produce are harder to watch and follow. While pleasing viewers is nice, it should not come at the expense of the creator's joy and identity. Finding and maintaining that boundary and balance can be difficult, especially as the influencer's brand grows. Playing the Algorithm One additional factor to consider is the platform an influencer is on—influencers who understand how their platform works can use it to their advantage and promote themselves more easily. Having a basic understanding of algorithms is often the key to achieving virality. One of the most studied platforms is YouTube: best practices on optimizing the algorithm, such as naming titles, thumbnails, and even how videos are posted, have been analyzed and shared across the platform. In theory, while these practices help everyone, they eventually turn into standards or "basic requirements" instead of real advantages. Not following these practices puts a creator behind the competition and sometimes can restrict the content creators make. Conversely, TikTok, as the newest big social media platform, has an algorithm that is still largely unknown. Creators are free to experiment with their content and formatting, but there is no way to tell if their practices will succeed, apart from basic metrics like impressions and engagements. However, it is essential to know that as these platforms develop, the algorithms will also shift. Keeping a keen eye on these shifts allows content creators to stay ahead and make changes as needed. It is also one of the reasons why creating content solely to go viral is a bad idea; desperately chasing the algorithm will only lead to burnout and compromise the legitimacy and authenticity of a creator's brand. At their most basic, social media platform algorithms are designed to capture and hold users' attention so the platforms can observe consumer behavior and target ads they think will be most relevant to them. To grossly over-simplify, these algorithms evaluate millions of factors to determine what they think each user will find engaging from the people and topics they follow. And they closely observe how users react to each piece of content -- scrolling past, slowing down, clicking, liking, etc. Users program their feeds essentially as long as what they're seeing keeps them on the platform. Keep this in mind as you create content for your audience: make sure the opening pitch is compelling (does your content grab attention in a second or less?), and does it inspire people to spend more time with your content? Listening to your audience Lastly, while it is beneficial to have a large following as an influencer, having a significant engagement is just as important, if not more. One way to do so is by listening to and engaging with the audience. Audiences that feel seen or heard are much more likely to watch or follow content while taking their suggestions and include them in the creative process. The interaction also builds community around the personal brand, offering more opportunities to show off a creator's expertise and further solidifying them as category leaders in their space. As a creator in the pursuit of a million dollars, it is easier to convince 1,000 people to give $1,000 each rather than trying to convince 1,000,000 people to give $1. Having a dedicated following gives creators more authority to monetize their brand, whether from brands or the viewers themselves. Ironically, being a creator is no longer solely about becoming as big as possible; as a creator grows more prominent, the connection to their viewing audience becomes smaller. Brands are starting to shift towards smaller creators with only tens of thousands of followers instead of hundreds of thousands or even millions of followers, as smaller creators can offer higher engagement at a more consistent frequency. Brands value the authenticity of a creator as much as the audience does; maintaining that essence while having a large following can be the most formidable challenge for a creator to face. Outro While there may be similarities between corporate brands and personal brands, ultimately, personal brands can reach others on a level where corporate brands cannot. A personal brand is both a tool and a reflection of the creators themselves; laying the framework for their brand puts a creator in the best position to succeed as an influencer and category leader. Even though the influencer industry may appear saturated, this peer-to-peer connection will always be valuable and occasionally necessary to get consumers to engage. About The Author Lomit Patel is the Senior Vice President of Growth at IMVU. Before IMVU, Lomit managed growth at early-stage startups, including Roku (IPO), TrustedID (acquired by Equifax), Texture (acquired. by Apple), and EarthLink. Lomit is a public speaker, author, advisor, and recognized as a Mobile Hero by Liftoff. Lomit’s book Lean AI , part of Eric Ries’ best-selling “The Lean Startup” series, is now available at Amazon .

How to Build Your Personal Brand as an Influencer and Creator 

Java Frameworks are the pre-written code body through which you are enabled to add your own code. There are numerous Java frameworks that have different leading features, on the basis of the same here, I will discuss Top 10 JAVA Frameworks For Web App Development 2021-2022. Frameworks provide a basic structure to the applications. Java Frameworks make developers' tasks easy as it has the tendency of managing the web app development process in a good manner and this finally helps them in delivering the projects on time to small, medium and larger enterprises. : Source Jetbrains Nowadays, most of the people prefer to hire Dedicated online Java app programmers to build a web app. Benefits of Using JAVA Frameworks : Java Frameworks provides top-notch security to the application, and it also allows to resolve the security issues in a faster way. Security : Java frameworks provide extensive community support where you can resolve your all doubts and issues; for this, you just need to post your query. Support : Generally, web app development tasks take too much time to complete, but this thing can be solved by making use of Java frameworks, it pre-defined functions makes the task easier. Efficiency : If we talk about cost, then framework maintenance cost is low. If the web app development coding part is easy, then the app development cost gets decreased. Expense Top 10 Popular JAVA Frameworks : Google Source Here I have listed Popular JAVA Frameworks that are mainly used by the developers. There are several Java app Programmer in India, and mostly all offer leading solutions to the enterprises (startups, SMEs, leading brands). 1) Spring Spring is one of the most popular lightweight JAVA Frameworks mainly utilized to develop Enterprise applications. This is the open-source framework that holds a lot of features, including security and configuration. The framework was initially released in 2002; that's why it has an active community. Spring Key Features Supports JDBC which helps in reducing the error Supports XML and annotation-based configuration Offers backward compatibility and testability of the code Makes J2EE development process simpler Leading Companies using Spring framework for application development Netflix (making use of Spring boot) Yatra (making use of Spring MVC) Amazon eBay 2) Struts Apache Struts is one of the robust open-source JAVA frameworks for web applications. It supports the Model-View-Controller (MVC) structure and prolongs the JSP API. Mainly there are two versions of this framework that are Struts 1 and Struts 2. Struts 2 is the upgraded version of Apache Struts, and that's why most of the companies prefer this framework. Key Features of Struts Manage app development process in an easy way. Offers Centralized Configuration. Allows to Integrate Struts with other Java frameworks that offer leading outcomes. Leading Companies using Struts framework for application development Infosys Accenture NexGen Technologies 3) Hibernate Hibernate ORM is an object mapping framework for Java. It proffers better communication possible between the relational database management systems (RDBMS) and Java programming language. Key Features of Hibernate Portability, productivity, maintainability Open-source framework It uses the JDBC API; helps in removing repetitive code. Offers ORM framework that helps in performing database operation on Java entities. Leading Companies using Hibernate framework for application development Oracle IBM DELL Accenture 4) Google Web Toolkit (GWT) Using GWT, developers can easily code complex browser applications. It also allows developers to develop and debug Ajax applications in Java. The remarkable thing about GWT is that you can write complex browser-based applications without being an expert in front-end technologies like JavaScript optimization or responsive design. Google Web Toolkit (GWT) Key Features Utilizes Google APIs Maintains complex JavaScript front-end applications Supports reusability of code Offers internationalization, cross-browser portability, bookmarking, UI abstraction and history management Leading Companies using Google Web Toolkit (GWT) framework for application development General Mills Inc Wal Mart Canada Corp Partners HealthCare System Inc Food Services of America Inc 5) Java Server Faces (JSF) JavaServer Faces (JSF) is one of the popular Java frameworks developed by Oracle for creating user interfaces for Java-based web applications. It’s an official grade of the Java Community Process (JCP) initiative. This framework supports UI components, and it is based on the MVC software design pattern. JSF  Key Features It’s an integral part of Java EE Offers excellent tools and vibrant libraries It allows you to extend existing backend Java code with a web interface. Helps in developing native applications. Leading Companies using JSF framework for application development Peoples United Bank Edupoint LLC Portland Water Bureau Spot LLC 6) Grails It is a dynamic Java framework developed by Groovy JVM programming language. The syntax of this framework is fit with Java, and it includes JVM (Java Virtual Machine) bytecode. This Java framework includes various technologies such as Spring, Java EE containers, Quartz, SiteMesh and Hibernate. It offers easy-to-read documentation; this helps developers in developing the applications. Grails Key Features Allow to build your own plugins and includes Grails IDE support for different platforms. Supports object mapping feature Allows you to reuse the code Offers flexible profiles Leading Companies using Grails for application development EasyCredito Secret Escapes Affectiva. AgoraPulse 7) Vaadin Vaadin is one of the widely used Java frameworks which mainly focuses on UX accessibility. By using this framework, you can develop the web applications of customizable components. From the Java Virtual Machine, it directly grants access to DOM. It is a lightweight framework known as Vaadin Flow, manages the routing and server-client communication. Vaadin Key Features Allow you to use MVC or MVP for data binding. Supports Drag and drop feature Supports Automatic server-client communication with WebSocket Supports JVM languages such as Kotlin and Scala Support Built-in Spring Leading Companies using Vaadin for application development Piksel Inc World Vision Inc Deutsche Post AG Quad Graphics Inc GESIS 8) Apache Hadoop It is not a full-stack framework; it offers a software framework and allows you to work on the MapReduce programming model. Its utilities can simply manage a large volume of data by storing, analyzing and processing. You might be thinking that why I have included Hadoop in the list, well I want to tell you that nowadays its leading feature of managing Big Data is obtaining prominence and that's why I have added this framework in the Top 10 JAVA Frameworks list. Apache Hadoop Key Features Offers Flexibility In Data Processing Easily Scalable Provides Faster Data Processing Hadoop Distributed File System (HDFS) Leading Companies using Apache Hadoop for application development British Airways Expedia Royal Bank of Scotland 9) Blade It is one of the best lightweight Java frameworks; it provides a full-stack web framework. This framework supports the MVC structure that grants the routing interface and makes the API cleaner to present everything in an easy way. This framework has a minimal impression means its source code is less than 500kb. Blade Key Features Supports web jar resources and plug-in extensions Support for configuring multiple files Holds CSRF (Cross-Site Request Forgery) and XSS (Cross-site scripting) Leading Companies using Blade Spookies Stormwatch Merengue Merengue 10) Dropwizard It is a high-performance Java framework that allows you to develop the web application. To make the development process faster, it together uses Java libraries. Dropwizard is a separate ecosystem that holds all the dependencies bundled into a single package. Dropwizard Key Features Allows to perform rapid prototyping Support open sources and independent libraries Quick Project Bootstrap Leading Companies using Dropwizard Upwork Channel.io Samba Tech Okta. SoFi Wrapping Up The Java frameworks that are mentioned here provide top-notch web app development service. If you want to develop an amazing web application for your business, then you can use the top Java frameworks as this will offer top security and structure to the application. If while developing the web app you are confronting any sort of issue then you can choose to . The experts have enough experience that they can develop the top-level application in a concise time frame. Best Java App Development Company India hire Expert Java app developers in India

Top 10 Java Frameworks For Web App Development: 2021 Edition

One-third of the total food produced is wasted according to the . It is approximately 1.3 billion tonnes and food scarcity is one of the major concerns globally. Isn’t it strange and funny? Food And Agriculture Association of the United Nations Once this issue came into the spotlight, 10 world’s largest food concerns like Unilever and General Mills pledged to share the success of their programs related to the curbing of food waste. Are you also facing the issue of excessive food wastage at your place? And looking for some innovative ideas to curb the food waste? In this blog we will be answering the following questions for every business operating in the food industry: What is the best technology for curbing food waste? What will happen if I do not follow a proper food wastage management process? What can AI do for reducing food wastage? What are the latest AI-Based applications available in the market which I can use for curbing food waste at my place? Are there any conglomerates which are using these AI-based apps? Companies all over the world are working on this issue after the United Nations told the world four years ago to half the total food wastage by 2030. There can be dire repercussions if this issue is not looked after immediately. Harmful results of not curbing food waste Food wastage has severe effects on the environment. If dumped in the landfill, it releases a greenhouse gas; methane. When the food degrades further it produces gases that are 25 times more harmful than carbon dioxide being trapped in the atmosphere. It results in global warming and nobody here is a kid to not understand how harmful it can be for climate change and ultimately for the planet Earth. Our resources require to be saved and food is an important resource for the survival of living beings. What are the best ways for food waste management? We are not in a very good state when it comes to food management even after a strict warning from the UN. According to last year’s , the food waste will rise by 70 percent on current values by 2050. World Bank report Image source The report said that this fact holds to be true only when there are no urgent steps taken immediately. In the past few years, various companies have started deploying Artificial Intelligence in the food industry to manage wastes. Businesses in the food industry and artificial intelligence development companies are working in this area to curb food wastage. The innovative ways with the help of this technology have provided remarkable outcomes. Role of Artificial Intelligence in Food Waste Management Artificial intelligence is all about developing computer-based systems that work with the same intelligence as humans. According to the Research and markets (the world’s largest market research store), the between 2019–2025 is forecasted to attain over 65.3 percent of CAGR. growth of AI in food and beverages industry Do you know how businesses and technologists are using Artificial Intelligence in food waste management? The trending technology of AI and its subsets like deep learning and machine learning are proficiently utilized in curbing food waste. For instance, recently, an artificial intelligence bin is launched by a UK based startup . This AI-bin uses a camera and smart scales to find the types of food that are being discarded. It is capable of reducing the food wastage by 50 percent and many businesses have availed this benefit. We will talk about this AI-Bin in detail later in this blog. — Winnow How AI helps in food waste management? Artificial intelligence technology-based software applications are capable of performing tasks which were only confined to the human mind. Its subset, machine learning is also playing an important role in reducing food wastage. ML works on vast data that helps in detecting types of food and their demands to manage them efficiently. These technologies are serving in unimaginable ways with various innovative tools. Let’s discover the various ways in which AI is used in the food industry, their benefits and the companies incorporating them. Following are the top uses of artificial intelligence in food waste management: Forecast food demandDetect the quality of the food sample Detect the food usually wasted 1. Artificial Intelligence in food waste management: Forecast food demand A bad demand forecasting can lead to heavy wastage in food. This is happening in supermarkets every day. You must have noticed how many food items get wasted in retail stores. To overcome this, the best in India are using machine learning in the food industry. ML works on algorithms based on large data. The data of previously wasted and sold food can help in forecasting demand. mobile app development companies This will help the supermarkets to stock the exact required amount of food. It will avoid more or less availability of food. Last year the came into a partnership with a hospital to avoid food wastage. Japanese company Hitachi The food not consumed by patients not only increases wastage but also poses harmful effects on their health. For this, they have mounted the camera on the trolleys which are used to collect the trays. Image source The camera clicks the pictures of leftovers. These photographs are later examined with the applications of deep learning (another subset of AI). This will help in identifying the patterns in leftovers which were not possible with the human mind alone. 2. Artificial Intelligence in food waste management: Detect food quality Have you ever returned a low-quality food? We all have done this many times! The same ingredients could have been used to produce an optimum quality for consumption. But unfortunately, a lot of food samples are not matching the quality standards which leads to food wastage. There is a company called which is based in the USA is using AI as a solution to this problem. They have their own food inspection system which is deploying the algorithms of deep learning. Agshift The deep learning models developed by hired software developers are capable of analyzing the defects in the sample quality. Sample images used here are a base to find out the overall quality of the food sample. 3. Artificial Intelligence in food waste management: Detect the food usually wasted The data of food that is thrown away most of the times can be an appropriate foundation to make new policies. It will help in reducing the supply of such food items. This collection is not possible with the help of human resources which brought the need for Artificial Intelligence in food safety. “A third of all food is wasted. It’s an economic, environmental and moral imperative that we reduce waste and know how it’s being wasted. We believe we have developed the answer to solve this for the hospitality industry.” said . Marc Zornes, the CEO of Winnow Here is a video of a TED talk by the CEO of winnow solutions. Have a look for a better understanding: https: //www.youtube.com/embed/BeDN5Jgg-G8 We discussed in brief about the AI-bin Winnow, let’s explore it some more. It is the first bin based on artificial intelligence technology to support the hospitality industry in its target of reducing food waste. It has reduced food waste with machine learning algorithms. The smart scales, AI-guided smart meters, and camera are used with AI technology. The system has been programmed to identify the thrown food. Whatever goes into the bin is not recorded anywhere. With the help of winnow vision, the companies can detect the food items that are discarded the most. Moreover, the AI-based bin is capable of calculating the environment and financial cost of the thrown items automatically. The solution it provides are: Improve food preparations methodsChange the menusBetter buying decisions There are many companies that have applied the technology of this marvelous system of contemporary times. Here are the popular use cases and outcomes: The first global chain of hotels that started using winnow systems is IHG resorts. Within six months, 50 percent of waste was reduced by IHG resorts through all the installations.23 stores of IKEA (food service organization) in the UK and Ireland has tested winnow and has successfully saved 1.6 million meals. Some more examples of companies using AI in food waste management: Utilizing Artificial intelligence to transform its production process of Whey protein. The manufacturers, based in Dutch, make sure to deploy the best technology to reduce food waste. With the help of new algorithms, they are also planning to improve their protein quality. DVNutrition : Serving more than 40,000 meals a day, Puget sound campus of Microsoft is using AI technology to log the items headed for the compost pile. This helps in the constant management of the orders. Microsoft: Final words: Artificial intelligence has made it possible for companies to reduce their food waste drastically. Its applications have allowed the food service organizations to become smart by forecasting the demand, detecting the quality and analyzing the thrown food. Undoubtedly, artificial intelligence is revolutionizing the food industry of modern times. If you are also willing to contribute to the environment like Microsoft and IKEA, then hire to get an AI-based software developed for your business to curb food wastage. our software development company Take a step further in making your business operations smart and healthy for society. You are most welcome to share your innovative ideas with us in the comment section. Let’s join hands to reduce food wastes. Always remember, there is enough for everyone’s need but not for everyone’s greed!

Why We Are Automating Food Waste Management With AI?

What best predicts whether the price of Bitcoin will go up or down? What if there was an algorithm that could predict this at least a day in ? This is what we’re building at the project and will be sharing how step-by-step. advance AlgoHive Just a quick refresher this project began with my initial post on how I created a Bitcoin prediction algorithm that produces a 29% positive return: _TL;DR: I’ve created a formula that predicts whether you should buy or sell Bitcoin based on daily exchange price data…_hackernoon.com How I Created a Bitcoin Trading Algorithm With a 29% Return Rate Using Sentiment Analysis This kicked off quite a few conversations on how best to improve and create a more robust algorithm. We now have a with investors, machine learning experts, data scientists and even beginners just wanting to follow along and learn more. thriving community The first project we’re working on is how build a Bitcoin prediction algorithm that gives a Buy/Sell signal for a given date with the intention to maximize profits. One of our data scientist community members, , an alumni of , is leading up the effort and is creating an open-source version of this . Laura Vargas CodingNomads BTC signal bot in GitHub What follows is our roadmap based on this code repository. The Bitcoin Signal API Roadmap Here is a quick glance at our roadmap: What’s Under the Hood The first step was determining the tools that will be used for the project. As this is an open-source project there were no shortage of great free tools to choose from most of which works seamlessly with the Python programming language. Our tech stack is built on open-source technology that work well with the underlying programming language: Python : an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language: Pandas _Edit description_pandas.pydata.org Python Data Analysis Library — pandas: Python Data Analysis Library : a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. It’s free and open source: Django _Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by…_www.djangoproject.com The Web framework for perfectionists with deadlines | Django : provides a simple interface for automating the downloading of reports from Google Trends. Main feature is to allow the script to login to Google on your behalf to enable a higher rate limit: PyTrends _Pseudo API for Google Trends . Contribute to GeneralMills/pytrends development by creating an account on GitHub._github.com GeneralMills/pytrends : Data visualization of our charts is currently leveraging Tableau Public — a great free way to visual and share data: Tableau Public _Tableau Public is free software that can allow anyone to connect to a spreadsheet or file and create interactive data…_public.tableau.com Tableau Public : An open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more: Jupyter Notebook _The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations…_jupyter.org Project Jupyter There’s lots of other components that you can see more in-depth. For full specs please see the in our Github repo. requirements doc How We Created the v1 Release Let’s walk through the setup steps as outlined in our roadmap: **Get historical transaction data for Bitcoin**There are many ways to obtain historical data for Bitcoin (BTC). In my original experiment I manually downloaded the crypto exchange data. In v1 we are automating the process by pulling BTC pricing data from the . This is a REST and WebSocket JSON API which is lightning-fast, has no rate-limits and is completely free to use! Here’s part of it in our implementation: Nomics API Using the Nomics API **Get Google Trends data**For the Google Trends data I originally manually downloaded the .csv from the Google Trends site. Here in v1 we are automating using , the unofficial Google Trends API. PyTrends is a Python library that scrapes Google Trends using custom parameters: PyTrends PyTrends API on GitHub **Import data into database**The project originally used PostgreSQL as the database but was changed to , a self-contained, high-reliability, embedded, full-featured, public-domain, SQL database engine. SQLite happens to also be the most used database engine in the world. Now that the calculations are processed in Python its no longer necessary to use PostgreSQL. In other words we can simply use a SQLite file instead of running a database server. SQLite **Identify Buy/Sell based on parameters identified in the article**My original article provides a Bitcoin Buy/Sell signal based on the combination of a Google Trends keyword ratio and BTC:USD price movement. This is going to be backtested further with more data from the PyTrends API. The goal is to find which ratio and price delta best predicts the Bitcoin price. Past performance of course does not necessarily predict future performance however it will be insightful to test several methods. In v1 we’re simply testing a fixed ratio and price delta (and converting to more dynamic variables later): **Use Django to create API**Django, as mentioned earlier takes care of the front-end web development. This service is currently used to serve-up a basic JSON API running on an Apache httpd service. Write API docs and publish One of the last major v1 goals is to write-up the API documentation then publish in the GitHub repository. This will provide detailed instructions on how you can connect to our API to get BTC Buy/Sell signals. This API will serve as a Bitcoin signal bot that you can incorporate into your own trading algorithm or investment formula. Although we have most of the basics published this will be updated regularly based on improvements and new features. Making Sense of the Data Through Visualization Although most of what happens in the algorithm is buried in the code many of these elements and data sources can be visualized. For instance here is the graph of the , and based on my original formula — to be further enhanced in v2: Google Trends Ratio Period Close Price Investment Value As this is refined we hope to better show positive or negative correlations to Bitcoin price and signals from other data sources. There is still lots of work to do to get to our first real MVP — . a trading signal bot that will profit from Bitcoin price movement Next Steps and Upcoming Features Although we have a long way to go we’re now just beginning work on v2 and since its open-source we’re inviting all though interested to contribute to the project. The good news is that you don’t have to necessarily be a coder to contribute. We are also beginning to compile a list of other ideas and data sources that we can eventually use for smarter price prediction. This first iteration primarily uses keyword indexing scores from Google Trends however there are several other sources that we will could incorporate including: A larger array of Google Trends keywords Sentiment analysis from Twitter Reddit forum activity Github repo activity BitMex data (Short vs Long volume) We may learn that there is no single best predictor of Bitcoin price appreciation or depreciation but some combination of a “golden ratio” instead. This is why we’re actively working on expanding our data sources and using machine learning to help backtest and expose predictive patterns in the data. How to Get Involved As we progress through our roadmap we’ll continue to share our progress and insights. The goal is to eventually release an API signal or bot that recommends Buy/Sell/Hold of Bitcoin at any given time to maximize profitability. This will have several use cases and the model can later be used to developed more advanced cryptocurrency prediction signals and indexes. If any of this interests you there is tons of work to be done and we can certainly use your help! Here are a few ways that you can get involved and join us in our epic adventure to the moon 🌕: : Help by contributing to our Bitcoin Signal project on GitHub. Developers improve the code : We’re starting to explore additional datasets and will need to perform a lot of backtesting, regression analyses and data modeling. Help us explore various data models to refine our algorithm. Join our growing here where all the magic happens! Machine Learning/Data Scientists Discord group : Have any new feature ideas or trading strategies that we could test? While this project is still a work in progress we would love to hear about what features you would like to see. Crypto Enthusiasts/Investors In the meantime please share our project with anyone who you think may find this of value. To get the latest updates on our progress follow me here on Medium as I share how we’re building this together step-by-step. 🚀 Any feedback is most welcome!

How to Build a Crowdsourced Bitcoin Price Prediction Algorithm

Los Angeles, November 2019. A cityscape littered with an innumerable amount of lights, with a haze of pollution covering the sky. Perpetual lightning storms block the sun from ever reaching the ground floor of the city. Violent flames burst from the peaks of chemical factories. A lonely, single vehicle flies across the night sky. The decadence of pure technological achievement, driven by greed and profit at the expense of humanity, contrasted with the plight of the everyman: . this is cyberpunk Along with being immersive windows into worlds of wondrous high tech achievements and the struggle of living in such worlds, cyberpunk media provides us a glance at the sheer horror of a future completely controlled by megacorporations. What would happen if you gave a centralized corporation (we’ll use Wells Fargo as an example, if only because they royally screwed up recently) say, the keys to human cloning? Grab a copy of Philip K. Dick’s and find out. The book doesn’t exactly spell it out, but this is what would happen: Wells Fargo would singlehandedly destroy the world’s food production while dooming our species to be replaced by physically superior synthetic humans. The horror in cyberpunk isn’t what happens to the characters — the horror is in the realization that our world could be headed down the same path as these cyberpunk dystopias. Who or what will keep us from sliding down this road? Do Androids Dream of Electric Sheep? Let’s look back at the cyberpunk novel: William Gibson’s reflects a future where extreme technological advancements are the norm, with corporate control permeating through every aspect of life. People use technology as an escape from reality, leaving their humanity behind. original Neuromancer. Neuromancer Cyberspace. A consensual hallucination experienced daily by billions of legitimate operators, in every nation. — Neuromancer (William Gibson) William Gibson’s Neuromancer The “cyberspace” presented in serves as a reminder that each of our senses — from our sight, hearing, smell, touch, to our taste — can be represented by a series of 0s and 1s. At their very core, sensations exist as pieces of data that travel to our brain in the form of electrical signals. There isn’t anything objectively special about smelling a sunflower; the line between the scent of a sunflower and the scent of a piece of steak may only be divided between some very small pieces of data. Neuromancer Now, we get into the horror aspect of ; what if cyberspace was controlled by megacorporations that exist only to churn out profits and exert dominance over other companies? The novel doesn’t go too much into sociopolitical aspects of cyberspace, but the implication is there: megacorporations exist on an almost totalitarian level. They control all aspects of life for citizens, ignore laws, and have monopolistic grasps over multiple markets. It seems too crazy to even imagine, but fear not! You don’t have to imagine. Neuromancer “The Illusion of Choice” — courtesy of on Reddit /u/mod83 Ten — count them. Ten. Coca Cola, Pepsico, General Mills, Kellogg’s, Mars, Unilever, Johnson & Johnson, P&G, Nestle, and Kraft control most of the world’s consumer goods. These names may not sound as threatening as “Tyrell Corporation” or “ Weyland-Yutani” and probably do not compete in as many industries as the megacorporations described in cyberpunk media, but they are getting there. What if Coca Cola decided to get into IT? What if Nestle decided to merge with AT&T? It seems ridiculous, but just recently Comcast attempted to purchase Time Warner Cable. It’s impossible to move, to live, to operate at any level without leaving traces, bits, seemingly meaningless fragments of personal information. Fragments that can be retrieved, amplified… — (William Gibson) Johnny Mnemonic The Alphabet (Google) logo reimagined as an evil megacorp (courtesy of ) 8th Mind We’ve only scratched the surface of companies that may one day become powerful enough to influence every aspect of human life. We haven’t even gotten into tech companies who hold monopolies over user data. Just recently, Google updated the Chrome browser to force anyone using Gmail or other Google services to also sign into the browser itself. When you’re signed into the Chrome browser, Google saves your web activity to their servers and uses it for whatever Googly reason they want. Google stated that this was done to fix cookie syncing issues and that users aren’t “fully” logged in during this scenario. However, the proverbial line in the sand with regards to privacy seems to have shifted and more tellingly, Google failed to call attention to the change in the first place. How do we stop Evil Corp from being the norm? It‘s probably impossible for anyone to predict when or how megacorporations will spring up into existence. An even more terrifying reality may be that we won’t even notice when certain oligopolies gain full control over the way we live our lives. With all this doom and gloom, what are we to do? Our first and final line of defense: Cryptopunks. Cryptopunks are blockchain enthusiasts who support decentralization projects not because of monetary interest, but because they believe in a future outside of the megacorp dystopia. Cryptopunks: regular people who happen to be fighting for our future. A natural extension of the cypherpunk movement, cryptopunks are activists for decentralization. They believe in social and political change through cryptography, blockchain technology, and truly trustless systems. Satoshi Nakamoto was a cypherpunk who created blockchain technology — cryptopunks are the adopters and supporters of the blockchain. More info on the cryptopunk movement can be found on this by Trent Lapinski of Hacker Noon. awesome write-up The key tenets of cryptopunks (decentralization, equality, transparent systems, personal privacy, and anti-corporatism) are all shared with the cypherpunks of old. The main difference between these idealistic movements lie within available technology. Cypherpunks were working with 90s era technology — a top of the line computer in 1995 had 8MB of RAM and a 33mhz CPU. Today, with advanced processing speed and the advent of blockchain technology, cryptopunks have a much better grasp at destroying and rebuilding inefficient old-world systems. As blockchain technology and hardware solutions develop, the power to truly decentralize the future and fight against corporatism lay at the fingertips of cryptocurrency enthusiasts. If you believe in the promise of crypto and actively support its use in demolishing corruption and greed in corporate systems, you are a cryptopunk. The battle has already started. This is the ballad of the cryptopunk. The future is already here — it’s just not very evenly distributed. — William Gibson

Ballad of the Cryptopunk

Welcome to the first post in my series of commentaries on the AR industry. My goal with this series is to give an inside look into the field, from the basics of the technology and the math behind it to the startups turning AR into a reality for consumers. This week, I’m diving into , an Augmented Reality startup helping to create AR marketing experiences and games for clients in all industries. Zappar : Quick Facts Founders: , , Caspar Thykier Connell Gauld Simon Taylor Funding: $3.75 Million Investors: , , (now ) You & Mr Jones Brandtech Ventures iDreamsky Technology Hargreave Hale Canaccord Genuity Wealth Limited Mission: “Zappar is a clever little app that can see and recogniseimages and objects in the world around us.” “We make Augmented, Virtual and Mixed Reality experiences for some of the world’s biggest brands.” Employee Count: 11 to 50 Focus: Creating AR experiences for clients and creating platforms which democratize the creation of AR experiences Zappar has created one of the premier mobile platforms for AR experiences. The Zappar app allows users to scan any “zapcode” (a proprietary QR code), and jump into an AR experience (a “Zap”) on their device. Zappar also acts as a consultant for companies who want to create a Zap to advertise their brand/product, such as , , and . Angry Birds One Direction General Mills An example BMW ad made with the ZapWorks Studio tool , I wrote how “when the main medium of information dispersion moved from newspapers to radios, the initial advertisements were simply newspapers advertisements read aloud. A similar thing happened in the early stages of the transition from radio to TV. It takes a while for advertising methods to catch up to the new medium and fully take advantage of it.” Zappar is embracing the new advertising medium, and in the process, will be one of the first firms to know what works/doesn’t work in AR marketing. In a previous piece An example “Zapcode” But Zappar isn’t just some AR consulting firm. In addition to creating client experiences, Zappar has also been working on platforms so that developers can easily create their own Zaps. By having easy drag-and-drop tools for creating AR experiences, Zappar is successfully building up the content library available on its platform, moving towards the goal of making Zappar the go-to AR experience platform. If the Zappar app contains all of the best AR experiences, then users will have no reason to download any other AR platforms onto their devices. When talking about Zappar, one competitor cannot be ignored: . The two companies are following the same development path. Just like Zappar, Blippar specializes in creating AR marketing experiences for clients (such as PepsiCo, Nestlé, Heinz, and Coca-Cola). In addition, Blippar also provides a suite of tools for creating AR experiences that run on its platform. The large difference between the companies is size: compared to Blippar’s $99 million in funding, Zappar’s $3.75 million is negligible. Blippar The race is on to create the de-facto AR platform for mobile. I had the pleasure of speaking with Jeremy Yates, a Senior Business Development Manager at Zappar, regarding the company and the future of the AR industry in general. Ed: Is the main focus of the Zappar platform marketing for 3P clients right now? Or are there plans to expand into other industries, such as first-party games? Jeremy: It’s not a focus for us right now but not something we’d rule out. I’ve no doubt that AR will become a large part of first-party games in the coming years but for now, I feel full AR games are waiting for a piece of AR/MR hardware that is robust and affordable — something that isn’t quite there yet. Pokemon GO cleverly used AR as a very small part of a much wider maps-based game and it was, perhaps mistakenly, labelled an AR-game rather than a game with AR. At Zappar we have developed mini-games for a wide range of clients and have worked closely with Rovio on developing an augmented reality strategy to connect their game app, movie and brand partnerships ( ). We say ‘mini-games’ because we need to keep these experiences small so they can be accessed on the fly and work across as many devices as possible. We are not trying to compete with fully fledged games. more here Our mission from the beginning has always been to democratise augmented reality by making it as accessible and affordable as possible and we strive to help our partners and end users capture value using this amazing technology. We try to ensure that any zaps (our word for AR experience) can be accessed quickly and easily through the device that matters most to people — the smartphone. By and large, we are a B2B2C business in the sense that we work with brands & agencies to develop experiences for their end users, or they use our tools to create AR activations for their clients. Part of this mission has been to put the power in the hands of the content creators and over the last seven years, we’ve developed the most complete publishing and authoring tool made specifically for AR on mobile: . ZapWorks Ed: Zappar has been very generous to schools and students with large pricing discounts. In what other ways is the company trying to democratize AR? Jeremy: Aside from ZapWorks and ZapBox, the other area of democratisation is our exciting partnership with Shazam. We’ve worked closely with the amazing team at Shazam to launch their visual recognition element to the Shazam app. Working with Shazam we can take AR on mobile devices to a whole new level and bring AR discovery to their hundreds of millions of active users. Ed: You recently wrote an article “ .” What do you believe are the best methods for convincing schools to adopt such a new technology, when many schools still use outdated technologies to begin with? Overcoming the challenges of using augmented reality in education Jeremy: For me, the first part has to be offering an affordable solution. Budgets in schools and universities are becoming increasingly constrained and we worked closely with a number of educators to ensure our offering was a viable option for schools interested in the technology. We offer a discount on ZapWorks seats of over 70% to educational institutions and have seen a huge amount of interest from the educational community and offer annual access to students for just $2. The second challenge is to ensure you’re catering for a wide range of technical capability. We’ve had kids as young nine develop AR posters using and on the other end of the spectrum, we’ve had game-design students prototype 3D models using . ZapWorks Designer ZapWorks Studio Ed: Are there any plans for bringing the Zappar platform onto other devices, such as some of the upcoming AR/Mixed Reality headsets? Jeremy: It’s an area we’ve had an eye on from the beginning but the issue with additional AR hardware was always going to be the price tag. Microsoft Hololens was extremely exciting but what was less exciting was the $3,000 price tag. We’d definitely be open to exploring support of new headsets but for now, nothing has interested us more than Cardboard, simply because of its affordability. Google Inspired by Google Cardboard’s achievements in VR, we took on the challenge of democratising mixed reality at an affordable price and that was really how came about, which again leverages the device everyone has (the smartphone) using pieces of cardboard or ‘cardware’ as we’ve called them and it’s priced at $30. It’s been an extremely exciting area of the business for us and I’ve had the chance to work on some fantastic projects. We’ve developed some experiences that anyone can use through ZapBox but we’ve been extremely excited to see the developer community begin to build experiences for these. ZapBox Ed: What are your personal favorite zaps? Jeremy: My favourite zap has been the zaps we developed with Accuray. We have always encouraged our partners not to use AR for AR’s sake but instead to develop a strategy that solves problems and/or creates opportunity, with the Accuray project I feel we did both of those things. Accuray and Zappar in action Accuray, an oncology company, needed to show potential buyers all over the world their products in order to generate sales but when your products are machines the size of MRI scanners, the task of transporting them is not easy — and, moreover, takes the items out of action from hospitals. 2017 at Zappar Go follow Jeremy on LinkedIn , he’s got some great views on the direction of the AR industry as a whole. Want to chat more about AR? Follow me on Twitter

AR Weekly Dive — Zappar

Walter Bright, who designed D, wrote an article called “ ”. I love D and I respect Mr. Bright, but I disagree with nearly everything he says in it, mostly because D itself and Digital Mars’s work in general is (and should be) extremely atypical of the kind of programming language design that occurs today. So You Want to Write Your Own Language Digital Mars has been writing cross-platform compilers for decades (and when I was first getting into C on Windows in the early naughts, Digital Mars’s C compiler was the one that gave me the least trouble), and D was positioned as an alternative to C++ as a general purpose language. The thing is, most languages being developed today aren’t going to be C-like performance-conscious compiled languages that need to build binaries on multiple platforms and live in environments with no development toolchains (all major platforms either ship with a GNU or GNU-like UNIX dev toolchain or have a system like cygwin or homebrew that makes installing one straightforward), and trying to compete with C++ is not only technically difficult but also foolish for wholly non-technical reasons. Design The second piece of advice Mr. Bright gives is to stick relatively close to familiar syntax, in order to maximize audience. This makes sense if you are trying to compete with C++, as D does. But D is a great illustration of the problems with this approach: D does everything C++ does better than C++ does it, and yet it has failed to displace C++. The reason is that C++ is a general purpose language, like Java, C#, and Go (in other words, a language that performs every task roughly equally poorly) and the appeal of general purpose languages is that they allow one to trade time learning a language that’s a better fit for the problem for immediate implementation difficulty. In other words, most things that are implemented in C++ are done that way not because C++ is the best tool for the job, but instead because C++ is marginally better suited than the three other languages that everybody on the dev team has known inside-out for twenty years. D can’t compete because the whole point of a general purpose language is to appeal to devs who failed the marshmallow test & want to minimize the initial steepness of the learning curve. The domain of general purpose languages is crowded, and each of them casts a wide net: being technically better across the board than all of them is difficult, and without really heavy institutional support (like that given to C++ and Java by university accreditation boards & given to C# and Go by large corporations) being technically better will only give you a small community of dedicated fans and an isolated ecosystem. Writing a general purpose language is a bit like forming 2-person garage startup positioned against General Mills. Instead, it makes more sense to target some underserved niche: general purpose languages are necessarily bad at serving most niches, and the syntax changes necessary to serve such a niche better are generally all too obvious to anybody actually developing in such a niche. Iteratively identifying and relieving pain points in real development work is sufficient to vastly improve a conventionally-structured language. Cutting the gordian knot by introducing a wildly unconventional syntax that’s better suited for certain kinds of work can be even easier, since such a syntax is allowed to be poorly suited for work outside its domain, and since the syntax of conventional general-purpose languages is made complicated & hard to reliably implement by decades of pressure to be suitable for all kinds of very dissimilar problems. Syntax is the difference between a tea spoon and an ice pick. Rather than aspiring to being vice grips or duct tape, build a language that is exactly the tool you need, and allow it to be a poor fit for everything else. When beggining a language project, it makes sense to try to get it minimally functional as quickly as possible, so that you can dogfood it & start identifying where your model of suitability has flaws. So (in direct contradiction to Mr. Bright’s list of false & true gods) it makes sense to start off with the easiest syntax to parse and as few keywords as you know how to proceed with. As you write code in your language, you will identify useful syntactic sugar, useful changes to the behavior of corner cases, and keywords you would like to add — and none of these are likely to be the ones that were at the bottom of your bucket list initially, unless you’re sticking quite close to some known conventional language. suitable To mimic Mr. Bright’s format, here are some false gods of syntax: Tried and true / universally-familiar syntactic constructs. A language should not sacrifice the ease with which it caters to its niche in order to cater to people who don’t want to really learn it, but instead should have a syntax that minimizes the effort necessary to solve problems within its domain and that corresponds predictably to its operation. If a language is syntactically similar to some other language, this similarity should reflect a semantic similarity (i.e., a stack language is justified in looking like forth and a declarative logic language is justified in looking like prolog). Avoid making a functional language look like an imperative one or using constructions that are misleadingly/shallowly similar to ones from another popular language, and instead choose metaphors for best fit. Over-design / biting off more than you can chew. Start off with a minimally viable language and determine what needs to be added from experience. Over time the gaps will be filled in and your language will look less like an esolang and more like a general purpose language, unavoidably; making a sturdy foundation is easier if you start off with only a few elements and making them quite solid. (I’m not encouraging the kind of masturbatory minimization of keyword lists you sometimes see in forth implementations, where only one or two keywords are hard-coded and everything else is written in the language; however, starting off with functions, conditions, i/o, and simple mathematics is generally sufficient to start writing real code, and it’s generally possible to get a simple language from zero to capable of hosting a fibbonacci sequence function in an afternoon.) “Readability”. Reading any language is a learned skill; while you should know how to parse the language you’re designing (don’t make it too hard for yourself since you’re going to spend a lot of time puzzling over the proper behavior of code you yourself wrote), caring too much about lowering the initial learning curve of new developers will put more work on your plate and limit your flexibility. I know people who consider C++ easy to read, and even a very straightforward language like forth or brainfuck looks like line noise to someone who doesn’t know the trick to reading it. If your language is well-suited to some problem, you need to trust that developers will figure out how to read it, and having a simple syntax that doesn’t cater too much to beginners will help more seasoned developers understand complicated code later. Here are some true gods of syntax: Suitability. Be an ice pick, not duct tape. Simplicity. Parsing is hard enough without ambiguity and corner cases (for both humans and machines); create a simple foundational syntax with as little ambiguity as possible, and make sure every behavior you add is compatible with that foundation. Iterative development. Making a really minimal language is straightforward, but making a language that is useful for complex problems is hard; it’s much easier to add features slowly based on need than it is to determine all of the useful behaviors before starting development, and it’s much easier to test a small number of base features before building on top of them than to test a large complex language all at once. Implementation Regex is a very powerful tool, if you know how to use it. Lexing involves identifying character classes, which is exactly what regex is best at. I wouldn’t recommend writing large chunks of your language as regular expressions, or using nonstandard extensions like lookahead & brace matching (which break some of the useful performance guarantees of vanilla regex anyway), but regex is invaluable for lexing, and with care it can be invaluable for parsing as well. If you are writing your language implementation in C, using lex (or GNU flex) can be a great time saver. I wouldn’t recommend using Bison / YACC, personally — it’s possible to thread arbitrary C code into lex rules, and implementing parsing with this feature and a set of flags is much easier for simpler syntaxes than using a compiler-compiler. With regard to portability concerns, any major platform will have a development toolchain containing lex these days. Of course, if you go the forth-lite route and have nearly completely consistent tokenization along a small set of special characters, this is much easier. Forth-lite languages can be split by whitespace and occasionally re-joined when grouping symbols like double quote are found; lisp-lite languages with only a few paired grouping symbols can easily be parsed into their own ASTs. It is possible to design a series of regex match expressions and corresponding handler functions, and iteratively split chunks of code from the outside in. , and I recommend it only if your syntax requires very little context: the two different meanings of comma and period in Mycroft (as well as handling strings) made parsing this way complicated in some cases, but this kind of parsing is very well-suited for languages like lisp where all grouping symbols are paired and very few characters are special-cased. This is a style I find quite natural, but I understand that many people prefer thinking of parsing in terms of a left-to-right iteration over tokens; one benefit is that grouping symbol mismatch will be reported in the middle of a block rather than at the very end (i.e., closer to where the actual mismatch probably is located, for large blocks with many levels of grouping). I did this in Mycroft In all of these cases, you should make sure that information about both position in the file & the tokenization & parsing context are available to every function, for error reporting purposes. If your syntax is sufficiently simple & consistent, this will be enough to ensure that you can produce useful error messages. Never expect any general purpose parsing or lexing tool to understand enough about your language to emit useful error messages; instead, expect to thread your own context through your implementation. I agree with Mr. Bright about the proper way to handle errors: rather than trying to make the compiler or interpreter smarter than the programmer, it makes more sense to exit and print a sensible error message. However, he doesn’t touch upon the difference between compile-time and run-time errors here, and in an interpreted language or one that is compiled piecemeal at runtime (which will be typical of the kind of language somebody writes today) the distinction is a little more fuzzy. Rather than, as Mr. Bright suggests, exiting upon encountering any error, I recommend keeping information about current errors (and the full call stack information related to them) and going back up the stack until an error handler is reached; if we completely exhaust user code and get to the top level, we should probably print the whole call stack with our message (or some large section of it). This is the style used in Java, Python, and sometimes Lua. It’s straightforward to implement (Mycroft does it , with ~10 lines of handling in the main interpreter loop and less than 40 lines in a dedicated error module), and it can provide good error messages and the framework for flexible error handling in user code (which itself can be implemented easily — see ). this way Mycroft’s implementation for the throw and catch builtins With regard to performance: it’s not that performance doesn’t matter, but instead that performance matters only sometimes. Machine time is much cheaper than enginer time, and so a language that makes solving certain kinds of problems straightforward is valuable even if it does so slowly. A general purpose language has to run fast and compile fast in order to compete, but notoriously slow languages have become popular because they served particular niches, even in eras when processors were much slower and speed mattered much more (consider perl in the text-processing space — although, because of accidents of history, it took a positon better served by icon — or prolog in the expert system space; prolog was so well-suited to the expert system space that expert systems were prototyped in prolog and then hand-translated from prolog to C++ in order to avoid the performance overhead). Unless you make huge dumb performance mistakes (and as the success of Prolog, PHP, Python, and Ruby makes clear, sometimes even big dumb performance mistakes aren’t fatal), if you scratch an itch the performance won’t be a deal-breaker, and optimization can come later, after both behavior and idiom are appropriately crystallized. Using a profiler is overkill in early iterations of the language, and since there’s a general trend in hardware toward many lower-power cores, you may get significantly more performance benefit from making parallelism easy to use (as Go does) than from tuning the critical path. Lowering Lowering is just an inverted way of looking at keyword minimization. When several mechanisms perform the same basic task with only small differences (as is the case with the three big looping constructs in imperative languages that Mr. Bright mentions), it makes sense to write a general function and then write syntactic sugar around it for the other cases, and if for some reason you have failed to do it that way in the first place then refactoring it (i.e., lowering) makes sense. However, I would recommend spending more initial effort identifying how to write well-factored builtin functions in the first place, rather than iteratively refactoring redundant code, because you will save debugging time & avoid problems related to minor differences locking in separate implementations that should be merged (for instance, in Python not only are dictionaries separate from objects, but there’s also a distinction between old-style and new-style objects, even though implementing objects and classes as a special case of dictionaries as Javascript and Lua do would make more sense). Runtime library Nearly all of Mr. Brights points about runtime libraries only really apply to languages competing with C++. He focuses on low-level stuff necessary for cycle-heavy processing on single cores, but this is almost entirely irrelevant to most of the code that gets written these days. Here are my suggestions: String I/O should be unicode-aware & support utf-8. Binary I/O should exist. Console I/O is nice, and you should support it if only for the sake of having a REPL with readline-like features. Basically all of this can be done by making your built-in functions wrappers around the appropriate safe I/O functions from whatever language you’re building on top of (even C, although I wouldn’t recommend it). It’s no longer acceptable to expect strings to be zero-terminated rather than length-prefixed. It’s no longer acceptable to have strings default to ascii encoding instead of unicode. In addition to supporting unicode strings, you should also probably support byte strings, something like a list or array (preferably with nesting), and dictionaries/associative arrays. It’s okay to make your list type do double-duty as your stack and queue types and to make dictionaries act as classes and objects. Good support for ranges/spans on lists and strings is very useful. If you expect your language to do string processing, built-in regex is important. If you provide support for parallelism that’s easier to manage than mutexes, your developers will thank you. While implicit parallelism can be hard to implement in imperative languages (much easier in functional or pure-OO languages), even providing support for thread pools, a parallel map/apply function, or piping data between independent threads (like in goroutines or the unix shell) would help lower the bar for parallelism support. Make sure you have good support for importing third party packages/modules, both in your language and in some other language. Compiled languages should make it easy to write extensions in C (and you’ll probably be writing most of your built-ins this way anyway). If you’re writing your interpreted language in another interpreted language (as I did with Mycroft) then make sure you expose some facility to add built-in functions in that language. For any interpreted language, a REPL with a good built-in online help system is a must. Users who can’t even try out your language without a lot of effort will be resistant to using it at all, whereas a simple built-in help system can turn exploration of a new language into an adventure. Any documentation you have written for core or built-in features (including documentation on internal behavior) should be assessible from the REPL. This is easy to implement (see ) and is at least as useful for the harried language developer as for the new user. Mycroft’s implementation of online help After the prototype If your language is useful, you will use it. Maybe some other people will as well. Writing a language is a great learning opportunity even if nobody uses it, since it improves your understanding of the internals of even other unrelated languages. Unless you are selling some proprietary compiler or interpreter (something that even Apple & Microsoft can’t get away with anymore) adoption rates don’t actually matter, except for stroking your ego — which is great, because there are a lot of languages out there and relatively few people are interested in learning obscure new ones. If your language gets any use, it will grow and mature into something harder to predict as behaviors change to be more in line with the desires of users (even if the only user is yourself). When languages grow too fast or are built on top of a shaky foundation they can become messy, with new behaviors contradicting intuition; some languages have taken a tool-box approach and embraced this (notably Perl and to a lesser extent TCL), and other languages merely suffer from it (notably PHP and C++). It makes sense to try to make sure that new features behave in ways that align as closely as possible to idiom, and to develop a small set of strong simple idioms that guide all features; that way, pressure to become general purpose won’t make the learning curve for new users too rocky. is how hackers start their afternoons. We’re a part of the family. We are now and happy to opportunities. Hacker Noon @AMI accepting submissions discuss advertising & sponsorship To learn more, , , or simply, read our about page like/message us on Facebook tweet/DM @HackerNoon. If you enjoyed this story, we recommend reading our and . Until next time, don’t take the realities of the world for granted! latest tech stories trending tech stories

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