GenAI Can Help Companies Do More with Customer Feedback

GenAI empowers agents to become instant experts in the consumer they’re serving and the specific questions they’re handling. For example, 61 percent of customer service and support leaders expect headcount reductions of only five percent or less due to GenAI. It should also be able to analyze historical customer service conversations with AI to discover what priorities the brand should address. For example, a customer messages a company’s support chatbot and is upset about a delayed refund for shoes that the customer returned. The chatbot would recognize the negative sentiment, gather relevant information on the message, and initiate an expedited refund process for the shoes.

The role of AI in contact centers today has evolved from a supplementary tool to a core component of delivering superior customer service. As consumer expectations rise for fast, personalized and seamless interactions, contact centers have turned to AI to remain competitive. Generative AI directly elevates the customer experience by facilitating highly-personalized interactions that make customers feel valued and understood.

So you and I could listen to the same call, and we could have very different viewpoints of how the call went. And agents, it’s difficult for them to get conflicting feedback on their performance. And so artificial intelligence can listen to the call, extract data points baseline, and consistently evaluate every single interaction that’s coming into a contact center. It can also help with reporting after the fact, to see how all of the calls are trending, is there high sentiment or low sentiment? And also in the quality management aspect of managing a contact center, every single call is evaluated for compliance, for greeting, for how the agent resolved the call. And one of the big challenges in quality management without artificial intelligence is that it’s very subjective.

Extracting Insights from Customer Feedback

Initial generative AI solutions only allowed companies to provide immersive, personalized experiences through text. They can deliver more creative, personalized, and human-like responses to customer questions and even help create engaging self-help resources, such as articles and FAQs. The rise of tools for developing powerful gen-AI agents in the contact center will give business leaders more freedom to augment their existing human teams. So I think when you’re thinking about things like real-time guidance, and coaching and training, this is where it becomes really crucial. I mentioned this being interaction-centric and having everything on one platform, but having the ability to use that sentiment data or customer satisfaction data in multiple places can be very powerful.

Here’s your guide to the best ways you can leverage AI to enhance customer support, without falling victim to common implementation issues. On the one hand, its Enlighten Copilot technology supports agents in every step of their journey, guiding them through real-time interactions with contextual guidance to drive optimal outcomes. Avaya also allows customers to choose which large language model (LLM) they want to power the GenAI agent assist use cases across the platform. But, with agents dealing with difficult situations more frequently, it also creates a need for them to show more empathy and creativity, which can drain their energy. Moreover, as bot-led interactions become more prevalent, agents will play a role in training bots so they deliver a similar level of service. As such, new agents will feel more confident and require less training since agent assist lifts the burden of performing specific tasks.

As companies progress in their journey, GenAI can be used to address more complex use cases. One of the most significant additions to Sprinklr’s AI strategy is its Conversational AI+ capability, launched in 2023. A dynamic capability introduced to amplify self-service functionalities, Conversational AI+ allows enterprises to tailor solutions to their business’s AI maturity level. The third pillar is agent interactions – cases where a real human being is still required.

Optimizing Self-Service Experiences

Our initial journey involved an extensive startup phase, featuring a meticulous market scan and evaluation of multiple technologies and vendors over a year. The right speech-to-text technology and vendor were chosen through careful assessment, including live tests and simulations, ensuring a seamless implementation phase and saving precious resources. In that frenzy, contact center vendors pumped out many GenAI-fuelled features to seize the initial media attention and convince customers that it’s finally time to embrace AI. At its heart, the solution contains a wealth of anonymized contact center conversation data that NICE has pulled together and used to develop sector-specific benchmarks for many metrics. Also, customers don’t like filling in surveys; they generally prefer low-effort experiences.

The company claims that Z-FIRE can derive specific insights into an individual’s property. With these insights, Metlife could understand what mitigation activities the owner engaged in and if the property was constructed using less combustible materials, potentially mitigating fire damage. Natural disaster risk more broadly further prompted MetLife to pursue emerging technology to accelerate underwriting operations, leading to their partnership with ZestyAI. Zesty AI is a software development company that offers property risk analytics via deep learning models. Humans may not have the upper hand on reading, understanding, and predicting emotions, but machines are a step ahead of humans in this paradigm.

AI is a powerful tool for companies who want to gather more insights into their target audience, and the opportunities they have to grow. AI solutions can process huge volumes of data from thousands of conversations across different channels, offering insights into topic trends and customer preferences. Perhaps one of the biggest use cases for AI in customer support, is that it allows companies to offer 24/7 assistance to customers on a range of channels. AI chatbots, for instance, are available to answer questions and deliver self-service resources to customers around the clock.

High-priority issues, especially those expressing strong negative sentiments, can be escalated to ensure they are handled promptly and effectively. At this stage, most contact centers still use a combination of AI IVR, chatbots, virtual assistants and human agents. But, when it comes to the human aspect of the contact center, a different form of AI is improving the customer service experience.

AI can absolutely create new efficiencies, and we do need them in healthcare contact centers. But we’re talking about conversations that can be deeply personal, and some of them always require human interaction. We designed Talkdesk Autopilot to perform tasks patients request, but also to seamlessly bring in human agents when necessary. We make it easy for nontechnical staff to monitor and optimize how genAI works in their contact centers, training and augmenting the model as new opportunities or challenges arise with clicks, not code. AI is listening in as a copilot for the agent, pulling up recommendations and suggesting answers based on the organization’s knowledge base.

The 3 Pillars of GenAI in Contact Centers

There’ll be a growing focus on securing and protecting the data fed to generative AI bots and ensuring these systems can align with existing compliance standards. Additionally, businesses may need to invest extra time and resources into monitoring the responses of the generative AI systems. Watching for signs of AI hallucinations will be crucial to preserving brand reputations. Alongside consistent omnichannel experiences, today’s consumers expect high levels of personalization.

We’d love to hear about your challenges and share how AI can galvanise your business. With real-time generative AI translations, contact centers can deliver culturally nuanced and consistent support to customers ai use cases in contact center worldwide, without additional costs. Managing a comprehensive contact center is becoming increasingly challenging in today’s world, as consumers connect with businesses through a wide range of channels.

Overall, BPOs offer other industries a look inside their potential futures with AI adoption — especially after the outpouring of interest in GenAI when ChatGPT was launched in late 2022. Metrigy found AI adoption was lower than anticipated in 2023, with 36% of all organizations using AI in their contact centers, compared to 70% of BPOs. This experience puts BPOs in a position to aid other organizations — including their own clients — in their own AI adoption strategies. Many BPOs also report using generative AI in their workflows for tasks like meeting transcripts, content creation for self-service channels or summaries for customer feedback.

By leveraging data analytics, businesses can pinpoint underlying issues and take proactive measures to address them, enhancing overall customer satisfaction. Sprinklr, a leader in Unified Customer Experience Management, harnesses the power of GenAI by integrating their own proprietary AI, built specifically for customer experience, with ChatGPT App Google Cloud’s Vertex AI and OpenAI’s GPT models. This enables Sprinklr to redefine the customer experience for their enterprise clients; offering various capabilities tailored to different use cases and business phases. Word processing and spreadsheets revolutionized workplace productivity across all parts of the organization.

Excessively focusing on AI might lead to insufficient human oversight, resulting in errors during customer interactions or a failure to empathize with customers’ needs. Real-time insights and analytics from GenAI systems help organizations fine-tune operations through consistent monitoring of key performance indicators (KPIs). By having immediate data access, managers can spot issues as they arise, such as service levels declining due to low staffing, and take corrective actions promptly. This enables contact centers to make proactive adjustments for better service delivery and optimized operations. Automated customer service interactions sometimes break down when customers change their intent halfway through a conversation – confusing the virtual agent. Our sister community, Reworked, gathers the world’s leading employee experience and digital workplace professionals.

That is a proposition that appeals to SMBs and Enterprise customers, in addition to the partner community. For instance, the traditional “Press One for… Press Two for…” IVR is transitioning to fluid, intelligent voice bots. However, the second wave of contact center platforms did little to inspire enterprises to take them on. There are several reasons, including tricky migration loads, regulatory quagmires, and data security concerns. Managers need to be guided on how to leverage these features, helping them understand and activate the value.

As such, businesses may now fundamentally rethink how they solve customer queries – which will, hopefully, entice more of those wave one contact centers to take the CCaaS leap of faith. Currently, though, many businesses lack the data discipline to leverage this potential fully. Contact center work relies on the natural language and information retrieval capabilities that genAI is designed for, notes Senior Analyst Christina McAllister. This week on What It Means, McAllister discusses how genAI could transform contact centers and what leaders need to do to capitalize on its potential. Generative AI cannot fully replace humans because it lacks the insight, oversight, and judgment that people provide.

Spotting Gaps In the Knowledge Base

Finally, one of the key areas where AI excels in the contact center, is in processing data, and making insights more accessible to teams and business leaders. With the right AI tools, companies can collect valuable information about customer experiences, sentiment, and employee performance across every touchpoint and channel. The shift toward AI is driven by both the need to handle increasing interaction volumes and the desire to provide a better overall customer experience. AI-powered chatbots, intelligent automation and predictive analytics enable contact centers to operate around the clock, offering instant responses to common queries and predicting customer needs before they arise. This has been especially valuable in an era where digital channels such as chat and social media have become as crucial as traditional voice support, providing customers with self service options around the clock.

Conversational AI is emerging as a critical component of most modern contact center operations. Rapidly evolving algorithms are offering companies a range of ways to improve customer experiences, boost efficiency, cut costs, and even access more valuable data. Transparency is crucial in the ethical development of generative AI systems for contact centers. Customers need to be made aware when interactions are mediated or augmented by artificial intelligence.

And that lens, in having the data, is more powerful in keeping this customer-centric approach, or this customer-centric mindset. « There’s such an enormous amount of data available that without artificial intelligence as this driving force for better customer experiences, it would be impossible to meet customer’s expectations today. » With AR in customer support, customers can use their smartphones or AR glasses to overlay digital information onto the real world. You can foun additiona information about ai customer service and artificial intelligence and NLP. For example, in a technical support scenario, AR can guide a customer through a product setup or troubleshoot process by visually demonstrating steps directly on the device they are trying to set up. This kind of interactive guidance can significantly reduce the complexity and time required to resolve issues.

Rather than just automating tasks, AI actively supports human agents by suggesting next-best actions, providing real-time translation, and instantly retrieving knowledge. That enables faster, more accurate responses while elevating the quality of customer conversations. In this approach, virtual agents not only handle customer queries but also trigger and manage backend processes across different platforms. With conversational AI, it’s easy to boil the ocean – especially as the latest GenAI-powered chatbots connect with the business’s knowledge stores and autonomously handle various customer queries.

• This feature, for example, could be configured to report information about the purchasing history of a customer making an inbound call so the agent taking the call will have potentially valuable information when servicing the customer.
• You should be able to create multiple versions of your voice solution, to suit various needs.
• With the advent of AI-backed IVR, however, these automated voice systems are lowering call center wait times, assisting with unique caller problems, and improving overall customer call center and contact center efficiency rates.
• Some of the most advanced generative AI solutions today, such as Google’s new “Gemini” model, can understand and respond to content in various forms.

Google’s final innovation utilizes the CCAI insights solution that sits inside the CCaaS platform to enhance and modernize a company’s FAQ section. The Knowledge Assist tracks the conversation between customers and agents, determines what the customer’s intent and what the agent needs to resolve the query. Whether that’s by mapping customer intents, generating testing data, or enabling more contextual responses to customer queries.

The CommBox AI chatbot leverages conversational and generative AI to measure customer sentiment and uses this analysis to inform responses and action pathways, like generating a unique return label. To address this, they implemented a conversation intelligence solution to automate QA and drive more efficient, detailed, data-driven analysis. Significantly, conversational intelligence can also identify patterns faster – or better than an agent could – which means they can identify and offer the customer relevant opportunities, upsells, or recommendations. This process can be managed end-to-end, without involving human agents, saving time without compromising on tailored support. From there, they can use the conversational intelligence platform to spot pain points and address them via technology, process, or coaching changes.

In the future, CCaaS platforms will offer more of these use cases to enhance data quality for sales, customer success, and contact centers. The episode concludes with McAllister’s advice on actions that contact center leaders should take and tech investments that they should make now to ready their organizations for success with genAI in the future. Understanding agents’ workflows and where their sticking points ChatGPT are, she says, could surface near-term opportunities for improvement. Generative AI models can be trained to detect subtle patterns of equipment failures, which is valuable in predictive maintenance. Instead of relying on scheduled maintenance or waiting for problems to occur, manufacturers can use GenAI solutions to forecast issues and carry out maintenance only when necessary, reducing unplanned downtime.

Baby name expert reveals parents are picking names ending in ‘ai’

The best AI stocks to buy span chipmakers, software companies, cloud computing service providers and technology giants. Domino Data Lab helps enterprises expedite the development and deployment of data science work. The company provides tools for building and productizing generative AI, including model fine-tuning for privately training and refining commercial and open source models, and prompt engineering for using any gen AI service securely. RTB House goes beyond basic AI-powered marketing campaigns, informing each campaign with deep learning algorithms.

Metropolis is an AI company that offers a computer vision platform for automated payment processes. Its proprietary technology, known as Orion, allows parking facilities to accept payments from drivers without requiring them to stop and sit through a checkout process. Morningstar’s family of fintech brands and products supports investors on a global scale. AI powers the Morningstar Intelligence Engine, which is meant to simplify the process of tracking down specific information amid Morningstar’s abundance of investment data and content.

Best Data Analytics…

These tools allow businesses to convert raw data into actionable insights through intuitive visual representations and facilitate deeper understanding of data, contributing to business growth. Precisely is a data integrity company offering high-speed sorting, big data, ETL, data integration, data quality, data enrichment, and location intelligence solutions. The company’s primary objective is to guarantee the highest levels of accuracy, consistency, and context in data, supporting organizations in making decisions with utmost confidence.

Nexthink supports IT teams across industries through software solutions that help them quickly and proactively respond to issues that can comprise the digital employee experience. The company incorporated an AI-powered virtual assistant into the Nexthink Infinity platform to answer users’ questions and support ChatGPT troubleshooting efforts. Its KIQ Agent Assist solution serves as a copilot that provides service agents with personalized support for interacting with customers. The company also offers the KIQ Customer Assist solution, which is a chatbot that responds to customers’ questions and issues directly.

Google Recorder

That’s why it’s important to use Etsy as a part of your multichannel ecommerce strategy. Starting an Etsy shop with the perfect name can help you get a strong start selling online or expand your existing business. But while it’s a great platform, Etsy has its limitations, especially when it comes to communicating with and marketing to your audience.

These are just a few reasons why the generative AI market is projected to reach $1.3 trillion by 2032. Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more. For the robotics industry, AI is typically used to upgrade the capabilities and autonomy of robots, allowing them to perceive, learn, and adapt to their environments. AI-driven computer vision and sensor technologies enable robots to recognize objects, detect obstacles, and perform tasks with greater accuracy. The organization has developed a platform that collects and analyzes molecular, clinical, and genomic data from academic medical centers and community-based hospitals. Its primary focus is on oncology, but it has expanded its solutions into other areas, such as infectious diseases and mental health.

Algorithms also analyze market data in real-time, letting traders base decisions on sophisticated data models. Additionally, AI powers robo-advisors that offer investment advice, wealth management, and more. Via Science, Inc., better known as VIA, is a U.S.-based startup specializing in Web3 technologies built on privacy-first principles. It creates and applies next-generation machine learning and simulation platforms to solve big data problems in various industries. VIA uses AI to connect smart meters, drones, and sensors to energy assets that are processed and checked to predict energy demands, grid loads, outages, and how much renewable energy is generated by solar panels and wind turbines.

OpenAI added that businesses may choose to strip out names before feeding resumes into a GPT model. The company said it has published blog posts and system cards — which are like AI instruction manuals — describing its models, including their capabilities and limitations. OpenAI also regularly conducts adversarial testing and red-teaming on its models in order to probe how bad actors could use them for harm, it said.

New generative AI models process « prompts, » such as internet search queries, that describe what a user wants to get. Generative AI technologies create text, images, video and computer programming code on their own. Having struggled to generate new revenue from « copilots, » software companies are now turning to AI agents. So far, the biggest demand for AI chips has come from cloud computing giants and internet companies. AI impacts various areas of everyday life, taking the form of customer service chatbots, smart devices that regulate home environments and virtual assistants that can complete basic requests and retrieve information quickly.

• Because of this advanced intelligence, Sanctuary AI already has a partnership with auto manufacturer Magna International Inc. to deploy Phoenix as a general-purpose AI robot in Magna’s facilities.
• AI-driven algorithms personalize the user experience, increase sales and build loyal and lasting relationships.
• To help you cut through the frenzy, Business Insider put together a list of what leaders in the field are saying about AI — and its impact on our future.
• Marketing teams can then quickly compile and organize complex data, segment and target specific audiences and determine the best platforms to reach their ideal buyers.

Its platform is fully customizable but also easy to use, prompting over 180,000 customers to rely on monday.com as their internal communication tool. The company recently released its AI feature in beta, and users can use it for workload management and optimization suggestions, automation recommendations, and content generation. Freshworks is a cloud-based software-as-a-service (SaaS) company providing businesses with customer engagement solutions for sales, support, and marketing. Freshworks started as Freshdesk in 2010, offering a simplified approach to customer support software. It then expanded rapidly and went public in 2021, offering a suite of products, namely CRM and sales (Freshsales), marketing automation (Freshmarketer), and IT service (Freshservice). Freshworks integrates AI across its products platform with features such as intelligent ticket routing, anomaly detection, chatbot conversations, and predictive insights.

Examples of Humanoid Robots

The company uses technical machine learning in its products and starting in 2024, ThousandEyes began building an AI chatbot. Global marketing tech company Klaviyo uses generative AI, machine learning and data science tools throughout its platform to help brands efficiently engage customers and expand their digital reach. More than 143,000 companies around the world trust Klaviyo’s technology to optimize their marketing campaigns.

The name “AHeirloom” is particularly effective because it conveys a sense of timelessness and tradition, suggesting that the products are not just items for sale but cherished keepsakes meant to be passed down through generations. This name resonates well with customers looking for meaningful gifts, making it memorable and relatable. When setting up your Etsy shop, consider search engine optimization (SEO), as this impacts how visible your store is in search results.

One suggestion is that AI models could be trained on images in the public domain, and AI companies could forge partnerships with museums and artists, Ortiz says. These descriptions of the images are useful for people with visual impairments who use screen reader software, and they help search engines rank the images as well. This also makes them easy to scrape, and the AI model knows which images are relevant to prompts. Stability.AI, the company that built Stable Diffusion, trained the model on the LAION-5B data set, which was compiled by the German nonprofit LAION. Baio analyzed 12 million of the 600 million images used to train the model and found that a large chunk of them come from third-party websites such as Pinterest and art shopping sites such as Fine Art America. Ascent offers services that use AI to power businesses efficiently and with automations that can efficiently manage regulatory compliance.

Will home robots (beyond vacuums) take off in the next decade?

So the race is on to build AI chips for data centers, self-driving cars, robotics, smartphones, drones and other devices. Companies will aim to boost productivity by developing customized AI for specific industries. The software programs aim to mimic the human ability to learn, interpret patterns and make predictions. Also, for most big application software companies, how to charge for AI-related products has been an issue. In general, semiconductor plays have out-performed software companies as the best AI stocks.

• Dr. Shahshahani earned his Ph.D. in Electrical Engineering from Purdue University in West Lafayette, Ind.
• On the manufacturing side, GM uses AI-driven predictive analytics to detect manufacturing problems before they occur.
• WriteSonic automatically generates SEO-friendly marketing copy for everything from long-form articles to social media ads to website landing pages — all of which is guaranteed to be plagiarism-free by the company.
• With all the buzz surrounding « generative AI » in the tech world, perhaps you’re one of the estimated 100 million users of ChatGPT, the artificial intelligence-powered chatbot from OpenAI.
• Google’s experiments with artificial intelligence have yielded a breadth of products, including Gemini.
• Some $6 billion of it came from Walmart for Symbotic to deploy even more of its technology.

As parents are opting for more uncommon names, some people are trying to claim baby names and ban friends and family from taking the name they want for their child — sometimes before they’re even expecting. The expert explained that “names that end in ‘ai’ are easily pronounced in many languages, including indigenous languages, European languages, Japanese, and African languages,” Kihm told Business Insider. AI is transforming the automation and transportation industries, reducing accidents and improving safety with real-time updates and traffic data. It’s also essential in predictive maintenance, as it can identify patterns in vehicle sensor data to keep fleets running efficiently for a longer period. AI is also the backbone of self-driving cars, harnessing features like computer vision, sensor fusion, and algorithms for decision-making.

Tempus has built one of the world’s largest libraries of clinical and molecular data, which is used to help physicians make more informed treatment decisions. Enlitic is a healthcare AI company that concentrates on data management applications, particularly on radiology. It uses AI to manage, process, and share medical imaging data, ultimately enhancing healthcare delivery and decision-making. Enlitic’s product suite includes ENDEX for standardizing of data from medical images, ENCOG for protecting patient information, and ENCODE for refining data quality. This company addresses data inconsistencies and has a strong commitment to data security.

More than 194,000 businesses in more than 120 countries use HubSpot, ranging from software and technology to education and nonprofits. HubSpot currently features an AI assistant in a public beta version for task automation, optimizing workflows, content generation, and data analysis. You can foun additiona information about ai customer service and artificial intelligence and NLP. Hostinger offers domain registration services for an impressive array of over 3,000 international domain extensions, including the increasingly popular .AI domains.

VIA also leverages machine learning and AI to enhance Web3-native security and privacy, which minimizes data storage needs, improves user data sovereignty, and secures Web2 apps against threats. Using AI in e-commerce allows companies to better understand customers and identify new trends. With AI, businesses can analyze web browsing patterns, buying history, and social profiles and tailor product suggestions and marketing campaigns based on these data.

“AI has been used as a buzzword to drive share price premiums, but companies have not always demonstrated usage of cutting-edge techniques,” he said. In early 2023, some small companies have seen rapid increases in their stock prices after being mentioned in any kind of AI-related news. In January 2023, for example, BuzzFeed (BZFD) saw its stock price soar more than 85% the day after the publication of a news report about a partnership with OpenAI to develop an AI-powered best names for ai article writer. But others are diversified ETFs that use AI-powered trading, and are not necessarily invested in AI stocks. “So far, we’re sticking with more of the mega-cap tech companies,” Brenner says, referring to FBB Capital Partners’ AI portfolio. This may influence which products we review and write about (and where those products appear on the site), but it in no way affects our recommendations or advice, which are grounded in thousands of hours of research.

Snapchat’s features include the My AI chatbot that was built on OpenAI’s ChatGPT technology. Users can exchange messages with the conversational AI and provide feedback to inform its continued improvement. Grammarly uses AI to help people produce written communications that are clear and grammatically correct. For business users, Grammarly’s writing partner can assist with creating on-brand marketing copy, for example, or effectively communicating company-wide technical updates. The technology also has applications for students, offering features to detect plagiarism and support accurate citations. WriteSonic automatically generates SEO-friendly marketing copy for everything from long-form articles to social media ads to website landing pages — all of which is guaranteed to be plagiarism-free by the company.

It also offers an AI art generator called Photosonic, a customer support bot called Botsonic and a GPT-4-powered AI chatbot assistant called ChatSonic. Bixby is Samsung’s AI personal assistant that runs on all its smartphones and some of its other smart devices, including refrigerators. Bixby is voice-based ChatGPT App and can be used for various tasks including texting, retrieving location-specific weather reports and reading news articles. Also referred to as virtual assistants, AI assistants bridge the gap between humans and the technology they use, simplifying users’ routines and enhancing their productivity.

Waymo, formerly known as the Google self-driving car project, is a subsidiary of Google’s parent company, Alphabet. Its flagship product, Waymo Driver, features a suite of sensors and software that enable mobility and safety from traffic crashes. It also operates Waymo One, a fully driverless robotaxi serving multiple cities that is fully electric and powered by renewable energy. Waymo stands out in terms of rigorous testing and deployment, with over 20 million miles of real-world driving experience, resulting in massive data for refining their AI systems.

Developed by NASA and General Motors, Robonaut 2 is a humanoid robot that works alongside human counterparts in space and on the factory floor. More than a decade ago, Robonaut 2 became the first humanoid robot to enter space, and worked as an assistant on the International Space Station until 2018, when it returned to Earth for repairs. Today, Robonaut 2 is inspiring other innovations and advancements in robotics, like the RoboGlove and Aquanaut from the ocean robotics company Nauticus.

The cloud giants in the September quarter notched revenue growth for the fourth straight quarter, indicating that AI investments may be paying off. Redflag AI makes a content protection platform that uses AI to search for and find instances of its clients’ owned content being used without permission. The AI looks at web content, checking for piracy, fraud, copyright infringement and cybersecurity issues, so that brands can maintain asset integrity and take appropriate action against copyright violators. For customers who are putting together a photo book, Mixbook has a generative AI tool that helps with caption writing. This feature of the Mixbook Studio can analyze a customer’s uploaded images and produce relevant caption options to help tell the visual story.

AEye, Inc. is a leader in LiDar technology for autonomous vehicles, advanced driver-assistance systems (ADAS), and robotic applications. AEye builds the vision algorithms, computer vision strategy, software, and hardware used to guide autonomous vehicles or self-driving cars. AEye’s adaptive LiDAR technology, iDAR (Intelligent Detection and Ranging), provides long-range, high-resolution sensing that is combined with real-time adaptability. This technology mimics how a human’s visual cortex focuses on and assesses potential driving hazards.