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An AI-powered tool that analyzes programs and generates meaningful trivial and non-trivial tests for developers to write bug-free codes.

About Codium AI

Codium AI is the first ever AI platform that interacts with developers to generate tests and explain the code. It saves developers from spending hours developing test cases, allowing them to focus on writing efficient programs.

Codium AI Features

Codium AI delivers several incredible features, making it one of the top-picks of developers. Some popular features offered by this tool are as follows:

It shows a real-time view of the output as you modify the code.

It saves developers time by generating meaningful test cases faster.

The tests check the code’s functionality to ensure it is of high quality.

It only analyzes the code that is to be processed.

It has an active community with members all over the globe. You can share your work with the community or interact with them to troubleshoot issues.

It allows users to download test cases as an extension for automation.

Codium encrypts your data to ensure 100% privacy and safety.

Codium AI Use Case – Real-World Applications

Codium AI is an essential tool in the coding industry. Some applications of this tool include the following:

Software developers can use Codium AI to write programs faster.

Quality Assurance Testers can use Codium AI to detect bugs within a program.

Companies can use Codium AI to ensure their software works properly. 

Codium AI Pricing


Does Codium AI understand all programming languages?

Unfortunately, Codium AI supports a few programming languages. It is a relatively new platform, so the developers are adding more programming languages to it. Currently, you can use it for JavaScript, Python, and TypeScript. Java will be added to the platform in the coming months.

How will my code in Codium AI remain safe?

Codium AI is an SOC2 certified platform. It ensures 100% privacy and security for your information. All your data will be encrypted before being stored on the system. Also, it only processes the necessary code, not your entire program.

Is Codium AI 100% right?

Codium AI uses artificial intelligence and machine learning algorithms to analyze the code and generate tests. The platform is programmed with powerful technologies, but nothing is perfect. So, you cannot rely on the Codium AI suggestions entirely. You must verify the test generated by the platform. If you find a bug, you can report it to the team and help them improve the tool.

Is Codium AI free?

Yes, Codium AI is available for free right now. You can start using it by creating an account on its official website. However, the company has announced that it will launch a paid plan for enterprises in the future. Until then, you can use it for free.

Who is the founder of Codium AI? Who is on its team?

Itamar Friedman and Dedy Kredo are the founders and CEOs of Codium AI. The tool is managed by a thriving and mission-oriented team of people from various tech giants, including Shopify, LinkedIn, Vine Ventures, Synk, and Espagon.

Codium AI is a powerful AI tool for developers, software companies, and businesses looking to create bug-free code faster. It saves the time of coders and produces high-quality programs, resulting in reliable and efficient software.

4.7/5 – (1348 votes)

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Top 4 Use Cases Of Ai In Fashion In 2023

Like every other sector, AI is also changing the fashion industry by offering solutions to various challenges. The global market for AI in the fashion sector was reported at $270M in 2023 and is projected to grow to $4.4B by 2027.

This article explores top AI use cases in the fashion industry to help business leaders in the sector learn where AI can be implemented in their businesses.

AI for design

Most companies in the fashion sector rely on clothing designs made manually. However, creative AI can be an effective way to take over in situations like the pandemic when people can not work. AI-enabled tools can create clothing designs by using data such as images from the brand’s previous offerings or from other designers, data regarding customers’ tastes (color and style choices), and current fashion trends.

Watch this video to see how the London college of fashion, amongst other institutions, is researching to find new ways to use AI for fashion design and production:

While extensive research is being done in this area, limited real-world applications of AI-enabled fashion designing can be observed, and all of the ones that exist are based on human-in-the-loop (HITL) models. 

For example, the German fashion platform Zalando and Google created project Muze, which uses machine learning to create fashion designs. The model gathers data regarding customers’ favorite textures, colors, and style preferences by asking a series of questions to create clothing designs.

The project created 40,424 fashion designs within the first month.

However, some found the designs created by the model strange and unwearable (See the image below).

But, with generative AI growing and improving at the speed of light, the design will soon be practical and considerable.

Improved production

Currently, the apparel manufacturing sector mostly relies on manual production processes with questionable working conditions for the workers. However, AI-enabled solutions are changing these trends by enabling automation in the apparel production sector.

AI can help overcome these ethical challenges by enabling automation. For instance, robotics can help automate risky or error-prone tasks in a manufacturing facility to decrease workload and improve worker safety. Companies like Sewbo and Softwear are revolutionizing clothing production by developing automated garment-producing machinery.

Moreover, computer vision enabled with AI also has various applications in fashion production, including efficient quality assurance and predictive maintenance of equipment which reduces the downtime of the machines and ensures operational continuity.

For more on AI training data collection, feel free to download our free whitepaper:

Trend forecasting

Fashion trend forecasting is the process of predicting possible future fashion trends. Traditionally, fashion trend forecasters combine their fashion knowledge, intuition, and historical data to predict possible fashion trends. However, measuring the accuracy of trend forecasts is difficult, and you can not know how accurate they are.

In the current digital era, AI is being used to accurately predict fashion trends using different types of data. For instance, the fashion tech company Heuritech developed an AI-enabled service to predict fashion trends by analyzing millions of social media images.

Watch the video to learn more:

Trend prediction can also be used to reduce wastage in the fashion and clothing sector by designing clothes people would actually want to wear. More accurate predictions can lead to leaner production and distribution cycles and less waste.

Improved fashion retail

AI-enabled technologies are widely used in fashion retail. The applications include:

Intelligent automation of repetitive back office tasks such as invoice creation can be automated.

AI-enabled computer vision systems can enable inventory management automation, retail theft prevention, cashierless automated stores, etc.

RPA also has various applications in retail, including improved customer relationship management and marketing operations.

Watch how H&M, one of the largest fashion retailers in the world, leverages AI to improve its operations:

Further reading

If you need help in finding a vendor for your business or have any questions, feel free to contact us:

Shehmir Javaid

Shehmir Javaid is an industry analyst at AIMultiple. He has a background in logistics and supply chain management research and loves learning about innovative technology and sustainability. He completed his MSc in logistics and operations management from Cardiff University UK and Bachelor’s in international business administration From Cardiff Metropolitan University UK.





Top 12 Sap Conversational Ai Use Cases & Applications In 2023

Business leaders are exploring conversational AI adoption in different departments due to its ability to facilitate processes and handle time consuming issues. SAP software which allows connection and collaboration across business departments can benefit from conversational AI capabilities.

The aim of implementing conversational AI in SAP is to make the user’s experience easier and simplify business interactions. Chatbot implementation in SAP enables better customer service, quick on-demand insights about business resources and data, facilitate issue solving, and simplify notification and alerts.

SAP Conversational AI solutions, which implement natural language processing, combine:

Using digital assistants to guide users through SAP processes

A chatbot building platform to build and test chatbots for different business purposes.

Conversational AI SAP solutions

System Applications and Products (SAP) is an Enterprise Resource Planning (ERP) software. SAP consists of business-specific models that allow users to collect and share data across business departments.

SAP digital assistant

SAP digital assistants leverage machine learning algorithms to allow the chatbot to learn from practice and become more contextually aware. Using a digital assistant within an SAP software enables:

Smooth collaboration across SAP modules (also called applications or models) by

providing faster access to information across business departments

Answering FAQs

Task automation by customizable workflows. Users can create custom chatbot intents to perform specific tasks

Better decision-making by providing operational insights

Personalized recommendations according to user behavior

Based on the user’s role/position, an SAP digital assistant can display reports, news, or alerts, as well as schedule meetings and invite different users to participate in a process.

Chatbot building platform

Chatbot building platforms allow users with minimal or no coding experience to build, train, and deploy chatbots. Nonetheless, in order to build a chatbot, the user must grasp the concepts of skills and intents which we explained in our article Intent Recognition in Chatbots in 2023.

SAP Conversational AI provides a platform to build or adapt end-to-end chatbots and integrate them with SAP ecosystem. The user can also use the platform to create chatbots from scratch to automate specific tasks in customer support, IT service, or purchasing. However, in order to build a chatbot, the user must grasp the concepts of skills and intents.

Leveraging SAP chatbot creating platform enables:

Faster chatbot creation, training, and deployment

Chatbot connection to multiple SAP solutions, external communication channels, or back-end systems.

Analysis of customers’ and employees’ communications to further improve users’ experience.

What are some conversational AI use cases in SAP?

Conversational AI can be implemented in the following SAP modules. We provide in-depth examples of their usage and briefly mention the business use cases these bots can serve. For more information on specific chatbot use cases, please refer to our articles on chatbot usecases by industry and by department.

IT department First level IT support

Many IT issues, that SAP users face, can be solved by simple solutions found in tutorials or SAP Help documents. However, users need the assistance of an IT professional to provide these documents and guidelines. Digital assistants in SAP systems can handle these simple tasks.

For example, MOD Pizza, an American fast casual pizza restaurant chain, used SAP CoPilot digital assistant to facilitate IT support processes. When a SAP system user requires IT support, the digital assistant provides links to tutorials or SAP Help documentations. The digital assistant can also direct the user to a live IT agent and send them information about the context of the problem, such as screenshots to facilitate problem-fixing.

Source: SAP user experience community

HR department

HR employees handle an enormous amount of employee information to which they may require access on the spot. An HR chatbot can retrieve employee information and visualize the data using SAP features. With this functionality, an HR chatbot can be used to answer:

FAQ on HR policies Complete HR requests like reserving Paid Time Off (PTO) Guide users through onboarding

For example, Nestlé, the world’s largest food & beverage company, used SAP conversational AI platform to create an HR chatbot. The HR chatbot provides self-service access to HR department data, such as headcount or full-time versus part-time hire ratios, in a secure and consistent approach.

source: SAP conversational ai tutorial

Customer service

SAP users in customer support department need access to different documents and information when responding to customer inquiries. Implementing a chatbot in customer support enables:

Management of multiple inquiries at the same time Provide accurate responses about products and services

For example, Groupe Mutuel, a Swiss insurance company used SAP conversational AI platform to develop a chatbot that can:

Respond to customer’s inquiries 24/7, in French and German through the company website

Enable end-to-end process integration and self-service scenarios for insurance and health plan members

For more on chatbots uses in healthcare, feel free to read our article Chatbot Applications / Use Cases in Healthcare in 2023

Sales & marketing

The sales and marketing departments can leverage SAP to measure marketing campaign results, and automate different marketing processes, such as email responses after cold calls.

Conversational AI in SAP marketing models can:

Serve as SDR

Sales development representatives (SDR) are the ones who initially speak to customers and book a product demo in B2B context. The demo would be run by a more experienced sales rep.

Chatbots can handle these tasks. they can converse with customers, provide product/service information such as pictures, videos, or links and schedule appointments for demos or trials.

Serve as sales reps

In B2C e-commerce, bots can even book tickets and flights.

For example, Expedia, an online travel shopping company, utilizes a Facebook messenger chatbot to offer customers a 24/7 agents who can book and manage trips, as well as provide COVID-19 updates about travel restrictions and airport openings.

source: expedia facebook messenger

Supply chain management

SAP models for supply chain management (SCM) have the following features:

Ability to collect data about different supply chain resources such as warehouses, inventories, shipments, and storage places.

Ability to connect suppliers, customers, manufacturers, business partners and retailers in one platform

Include different planning applications related to Advanced Planning and Optimization APO

Include applications for supply chain networking, supply chain planning and coordination, and supply chain execution.

Chatbots in supply management SAP models can:

Provide instant and accurate data about SCM resources Process supply chain employees’ requests

Chatbots can process requests based on supply chain data, such as tracking numbers and customer ID

Manage orders

Chatbots can directly collect new orders from customers, manage old/cancelled/delayed orders, and automatically update the supply chain database.

What to expect in the future?

According to our chatbot / conversational stats, 31% of executives said that virtual assistants have the largest impact on their business. Additionally, 75-90% of queries is projected to be handled by chatbots by 2023. This data suggests that SAP software will depend on conversational AI heavily across multiple SAP business models in the future.

Furthermore, implementing RPA along with conversational AI into SAP applications can drive the automation process in enterprise resource planning to the point where the user will only has to ask the chatbot what the next step is, and have the RPA bot take care of it.

For more on RPA in SAP, feel free to read our article Top 5 RPA Use Cases / Application Domains in SAP in 2023

For more on conversational AI

To learn how conversational AI and chatbots work, read our articles about natural language understanding, and top 10 voice recognition applications and use cases

For more on conversational AI successes, failures and market, feel free to read the following articles:

For a comprehensive guide on voice AI and chatbots:

If you think your business can benefit from conversational AI, let our data-driven list of chatbot vendors and chatbot platforms can show you which vendors you can start talking to.

And if you have questions about how chatbots can help your business, we can help:

This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.





10 Gan Use Cases In 2023

Some highly technical use cases, such as modeling probabilistic distributions or sampling from an arbitrary distribution, may be better suited for other types of generative AI models like Variational Autoencoders (VAEs) or Generative Stochastic Networks (GSNs).

However, most of the popular generative AI applications under use are performed by GAN. In this article, we will explain 10 GAN use cases.

Top 10 GAN Use Cases 1- Image generation





Figure 1: Generated image of “a running avocado in the style of Magritte”

Source: DALL-E

2- Image to image translation

GANs creates fake images from input images by transforming the external features, such as its color, medium, or form, while preserving its internal components (see Figure 2). This can be used as a general image editing method.

Figure 2: An example of facial attribute manipulation

Source: “FAE-GAN: facial attribute editing with multi-scale attention normalization”

3- Semantic image to photo translation

Figure 3. An example of semantic image to photo translation.

Source: “Generating Synthetic Space Allocation Probability Layouts Based on Trained Conditional-GANs”

4- Super resolution

GANs can improve video and image quality (see Figure 4). It restores old images and movies by upgrading them to 4K resolution or higher, generating 60 frames per second rather than 23 or less, removing noise, and adding color.

Figure 4: GAN-based restoration of images.

Source: “Towards Real-World Blind Face Restoration With Generative Facial Prior”

5- Video prediction

understand the temporal and spatial elements of a video

generate the next sequence based on that understanding (as shown in the Figure 5)

differentiate between probable and non-probable sequences

Figure 5. Prediction results for an action test split. a: Input, b: Ground Truth, c: FutureGAN.

Source: “FutureGAN: Anticipating the Future Frames of Video Sequences Using Spatio-Temporal 3D Convolutions in Progressively Growing GANs”

6- Text-to-speech conversion

Text-to-speech conversion technology has various commercial applications, including:





For instance, an educator can turn their lecture notes into audio format to make them more engaging, and this same approach can be used to create educational resources for those with visual impairments.

7- Style transfer

GANs can be used to transfer style from one image to another, such as generating a painting in the style of Vincent van Gogh from a photograph of a landscape (see Figure 6).

Figure 6. The cycleGAN generates designs in the style of different artists and artistic genres, such as Monet, van Gogh, Cezanne and Ukiyo-e.

8- 3D object generation

GAN-based shape generation allows for the creation of shapes that more closely resemble the original source. Also, it is possible to generate and modify detailed shapes to achieve the desired result. See the GANs-generated 3D objects in Figure 7 below.

Figure 7. Shapes synthesized by 3D-GAN.

Source: ”Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling”

The video below shows this process of object generation.

9- Video generation 10- Text generation

With the large language models, generative AI based on GAN model has a range of applications in text generation, including:


Blog posts

Product descriptions

These AI-generated texts can be used for a variety of purposes, such as: 

Social media content




In addition, it can be used to summarize written content, making it a useful tool for quickly digesting and synthesizing large amounts of information.

If you have questions about GAN or need help in finding vendors, feel free to reach out:

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.





Bing Chat Ai Brings New Features For Android And Iphone (Including Widget)

Microsoft is rolling out new features and changes for Bing Chat AI on mobile.

The update brings improvements to the Edge, Bing, Skype, and SwiftKey mobile apps.

Among other things, Edge mobile will now be aware of the web content you’re viewing.

Bing app gets continuous chat and mobile widgets, and SwiftKey gets a new Compose feature.

Microsoft has announced a new round of updates coming for its Bing Chat AI on mobile devices. In the release, the company is improving contextual chat for the mobile version of Microsoft Edge. Android and iOS users can access the chatbot using a new widget, and conversations now sync between desktop and mobile devices.

Microsoft Edge mobile

Furthermore, the browser also includes an option that you’ll soon allow you to select some text, and Bing Chat will summarize or explain it.

Bing app mobile

The second update brings the ability to continue the conversation across platforms. This means you can now start a chat on the desktop and then continue on your mobile device (and vice versa). For instance, you can query the chatbot about a recipe on the desktop and then continue on the phone at the grocery store, asking about an alternative ingredient.

As part of the expansion of the Bing Chat AI, Microsoft says that it has increased the country and language support for voice input and improved the quality of non-English chats.

In addition, the Bing app is getting a new Chat widget that you can add to your iOS or Android home screen. The widget will allow you to interact quickly with the chatbot using typing or voice. As you ask a question, the answer will appear on an overlay on the home screen.

SwiftKey app mobile

In addition to the recent AI integration, Microsoft is now bringing the Compose feature to SwiftKey. The new feature will allow you to draft content based on your suggested parameters, including tone, format, and length. For example, you can use this feature to email a service provider asking for a resolution on an issue. Quickly edit the drafted email to ensure the details are correct, then send it.

Furthermore, the SwiftKey app now includes a translator that uses AI to make it easier to translate content from different languages.

Finally, the keyboard is also getting two additional tones, including witty and funny.

Skype app mobile

Also, the Skype app for mobile is getting Bing Chat in group chats. If you still use Skype, you can now tag “@Bing” in a conversation, and the chatbot will respond to queries and conversations.

This new round of updates comes only days after the company announced several other features and changes for the Bing Chat AI experience.

For example, when asking a question, the chatbot can now include images in the responses to explain the answer better. Let’s say you ask Bing questions about flamingos or capybaras, then a picture of these animals will appear as part of the answer.

Microsoft has also updated the visual design for elements that appear at the end of text-based answers to improve the experience for shopping, weather, finance, and autos.

Furthermore, this update improves the copy-and-paste experience when Bing chat generates code or other blocks of formatted text. Also, when inserting a prompt into Bing chat, you can include formatting like paragraphs, bullets, or numbering.

Samsung Galaxy S7 Release Date And Pricing Confirmed

Samsung Galaxy S7 release date and pricing confirmed

After months of leaks, the details of Samsung’s Galaxy S7 and Galaxy S7 edge may not have been a complete surprise, but that won’t stop people from buying it in droves. All five of the major US carriers are signed up to sell the new Android flagship, and the good news if you’re itching for an upgrade from your current phone is that you won’t have too long to wait.

That’s because the Galaxy S7 release date is March 11th, though you’ll be able to stake your place in line earlier still. Pre-orders begin on February 23rd, which means there isn’t long to decide which carrier gets your business.

On AT&T, the Galaxy S7 will be $23.17 per month on the carriers’ Next 24 plan, for the 32GB phone. The Galaxy S7 edge also has 32GB of storage, and starts at $26.50 on the same plan. Oddly, given what the name would imply, both Next 24 plans run for 30 months.

Sprint will offer the Galaxy S7 for $27.09 per month for 24 months, or the Samsung Galaxy S7 edge for $31.25 per month over the same period. The carrier is also doing a promotion where buyers get a second handset of the same Galaxy they bought for half price, though that takes the form of a service credit.

The carrier’s budget brands will also get the phones, with Boost Mobile snagging both on March 11 too, while Virgin Mobile USA will follow on shortly after.

T-Mobile USA has priced the Galaxy S7 for $27.92 per month for 23 months and $27.83 for the final month, as part of its payments plan. The S7 edge will be $32.50 for 23 months, and then a final $32.39 payment. Alternatively, it’ll be offered on JUMP! On Demand for $32.50 per month for the S7 or $28 per month for the S7 edge.

T-Mobile says that the Galaxy S7 full retail price is $669.99, while the Galaxy S7 edge is $779.99.

Verizon has committed to the February 23rd (8 am ET) preorder date, but is yet to confirm pricing at this stage.

UPDATE: The Samsung Galaxy S7 will be available at Verizon with one plan starting at $28 per month for 24 months ($672 retail price). Meanwhile the Samsung Galaxy S7 edge will be released on a plan starting at $33 per month for 24 months ($792 retail price). Both devices will be available March 11.

NOW READ: Samsung Galaxy S7 hands-on

Finally, U.S. Cellular will have a 24 month payment plan option, with the Galaxy S7 for $28 and the Galaxy S7 edge at $32.50. However, there’ll also be two-year agreements, at which point the S7 will be $199 upfront and the S7 edge will be $299.

What there doesn’t appear to be, at least at this stage, is a way to buy an unlocked, SIM-free device from Samsung itself. We’ll let you know if that changes any time soon.

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