Category Archives: Ai

Have Insiders Sold SoundHound AI, Inc. (NASDAQ:SOUN) Shares Recently?  Simply Wall St

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Have Insiders Sold SoundHound AI, Inc. (NASDAQ:SOUN) Shares Recently? - Simply Wall St

Under the themes Shaping the Future with AI and Semiconductor and Scaling AI for the Real World, renowned experts will share the latest AI research achievements

Samsung Electronics today announced that it will host the Samsung AI Forum 2022 from November 8 to 9.

The Samsung AI Forum, now in its sixth year, is a place for exchanging technological advances with world-renowned AI scholars and experts, sharing the latest AI research achievements and exploring future research direction.

This years forum will be held in-person for the first time in three years and will also be live-streamed on Samsung Electronics YouTube channel.

Those who are interested in the event can register to participate in the forum from October 18 to the day of the event on the Samsung AI Forum website. Registered participants will be able to receive a detailed program agenda and submit questions online.

Day one will be hosted by Samsung Advanced Institute of Technology (SAIT) under the theme Shaping the Future with AI and Semiconductor. Participants will discuss the current status and research direction on AI that will lead the future of innovations in other fields including semiconductors and materials.

Jong-Hee (JH) Han, Vice Chairman, CEO and Head of Device eXperience (DX) Division at Samsung Electronics, will start the forum by giving the opening remarks, followed by a keynote speech from Professor Yoshua Bengio of the University of Montreal, Canada. Afterward, technology sessions, such as AI for R&D Innovation, Recent Advances of AI Algorithms and Large Scale Computing for AI and HPC will be held.

During each technology session, renowned AI experts and the AI research leaders at SAIT will be on stage to share their findings.Minjoon Seo, Professor at KAIST, and Hyunoh Song, Professor at the Seoul National University, will introduce the latest research achievements on AI algorithms, and the former IBM and Intel Fellow Alan Gara, who is one of the leading researchers on supercomputers, will make a presentation on the evolution of computing and the future of AI. AI research leaders at SAIT including Changkyu Choi, Executive Vice President and Head of SAITs AI Research Center, will share the status and vision of Samsungs research on AI.

This years AI forum will be prepared to be a place to discuss the direction of AI research to create a better future by applying AI technology to various fields, especially semiconductor, in the future. said Gyo-Young Jin, President and the Head of SAIT as well as Co-chair of the Samsung AI Forum.

The Samsung AI Researcher of the Year awards, which were established to discover excelling rising researchers in the field of AI, will also be presented during the forum. In addition, various programs, including poster presentations of excellent research papers, introduction of the SAIT, exhibition of its research projects and networking event for researchers and students in the field of AI will be held to accelerate active research in AI.

Day two of the forum will be hosted by Samsung Research under the theme Scaling AI for the Real World. Participants will share the direction of future AI technological advancement that will have an important impact on our lives, such as hyperscale AI, digital human and robotics technology, which are the latest trending topics.

Sebastian Seung, President and Head of Samsung Research, will start with a welcoming remark and a keynote speech on Evolutionary approach to brain-inspired learning algorithms.

Daniel Lee, Executive Vice President and Head of Samsung Researchs Global AI Center, will give a presentation on current status of Samsung Researchs AI research, which will be followed by invited talks by AI experts, including the heads of Global Research Institutes.

Terrence Sejnowski, Professor at the University of California San Diego and founder of NeurIPS (The Conference and Workshop on Neural Information Processing Systems), one of the most prestigious international conferences on AI, will speak on whether large language models have intelligent, and Dr. Johannes Gehrke, Head of Microsoft Research Lab, will explain the core technology of hyperscale AI and research directions of Microsofts next-generation AI.

Afterwards, Dieter Fox, Senior Director of Robotics Research at NVIDIA, will give a presentation on robot technology that controls objects without an explicit model and Seungwon Hwang, Professor at the Seoul National University, will share knowledge on robust natural language processing technology.

Furthermore, Daniel Lee will moderate the panel discussion on the latest AI trends and the future outlook with fellow speakers. There will also be times allotted for presentation and demonstration of the latest research status by the researchers at Samsung Researchs AI Research Center.

This years Samsung AI Forum will be a place for participants to better understand various AI researches currently underway in terms of Scaling AI for the Real World to increase the value of our lives, said Dr. Sebastian Seung, President and Head of Samsung Research. We hope many people, who are interested in the field of AI, will participate in this years forum, which will be held both online and in person.

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Samsung Electronics Explores Future of AI Research

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Eyenuk, Inc., a global artificial intelligence (AI) digital health company and the leader in real-world applications for AI Eye Screening and AI Predictive Biomarkers, today announced it has secured $26 million in a Series A financing round, bringing the Companys total funding to over $43 million.

The capital raise was led by AXA IM Alts and was joined by new and existing investors including T&W Medical A/S, A&C Foelsgaard Alternativer ApS, Kendall Capital Partners, and KOFA Healthcare.

Accelerating Global Access to AI-Powered Eye-Screening Technology

Eyenuk, Inc. is a global artificial intelligence (AI) digital health company and the leader in real-world AI Eye Screening for autonomous disease detection and AI Predictive Biomarkers for risk assessment and disease surveillance. Eyenuk is on a mission to screen every eye in the world to ensure timely diagnosis of life- and vision-threatening diseases, including diabetic retinopathy, glaucoma, age-related macular degeneration, stroke risk, cardiovascular risk, and Alzheimers disease.

Eyenuk will use the capital to expand its AI product platform with additional disease indications and advanced care coordination and to accelerate the platforms global commercialization and adoption.

We are thrilled that AXA IM Alts, T&W Medical A/S, A&C Foelsgaard Alternativer ApS, Kendall Capital Partners, and our other new and existing investors have joined us in furthering our mission of using AI to screen every eye in the world to help eliminate preventable vision loss and transition the world to predictive and preventative healthcare, said Eyenuk CEO and Founder Kaushal Solanki, Ph.D. Our Series A fundraise validates the strong market performance of the EyeArt system and provides us with critical resources as we expand our platform capabilities this year to include solutions for detecting additional diseases.

Todays announcement follows the Sept. 29, 2022 publication of a major peer-reviewed study in Ophthalmology Science, a publication of the American Academy of Ophthalmology. The study found that the EyeArt AI system is far more sensitive in identifying referable diabetic retinopathy than dilated eye exams by ophthalmologists and retina specialists.

Eyenuk is leading the way in harnessing the power of AI to eliminate preventable blindness globally, through its versatile digital health platform that enables automated AI diagnosis and coordination of care. Eyenuks flagship EyeArt AI system has been more broadly adopted worldwide than any other autonomous AI technology for ophthalmology. Since its FDA clearance in 2020, the EyeArt system has been used in over 200 locations in 18 countries, including 14 U.S. states, to screen over 60,000 patients and counting. It is the first and only technology to be cleared by the FDA for autonomous detection of both referable and vision-threatening diabetic retinopathy without any eye care specialist involvement.

The EyeArt system is reimbursed by Medicare in the US, and has regulatory approvals globally, including CE Marking, Health Canada license, and approvals in multiple markets in Latin America and the Middle East.

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Eyenuk Raises $26M for AI-Powered Eye Screening & Predictive Biomarkers

Video surveillance plays a vital role in the construction sector, and the rise of cloud video analytics, AI technology, and video surveillance as a service (VSaaS) offerings has the potential to take this to the next level. In this article, Logan Bell, head of product for Cloudview, shares the uses of AI and VSaaS and other benefits in the construction sector and how they are combined to improve the safety of the construction sector.

Health and safety are critical components of any business, but those in the construction sector need to take additional steps to look out for the safety of workers and protect their own construction firm from the potential financial, legal and reputational consequences associated with failures or shortcomings, in this area.

Video surveillance can play a vital role here, and the rise of cloud video analytics, artificial intelligence technology, and video surveillance as a service (VSaaS) offerings has the potential to take this to the next level. Lets look at precisely how AI and VSaaS are combined to improve safety within the construction sector.

First, it is essential to define precisely what is meant by artificial intelligence and video surveillance as a service. The former refers to technology that allows computers to perform complex actions, which have traditionally relied upon human intelligence, and is especially useful for automation and analysis of data.

VSaaS, on the other hand, refers to cloud-based surveillance services offered by third-party service providers. With a cloud-based video management system, users can remotely access the data captured by their surveillance system. Data is also stored in the cloud rather than on-site, allowing more footage to be stored while improving accessibility.

The two technologies can combine to provide cloud video analytics offerings. This will feed data from surveillance cameras through a layer of AI, pattern recognition, machine learning, and similar technologies to extract meaning from it and alert users to any actions, scenes, or situations deemed worthy of attention. As explained in an article from SDM, cloud deployment allows more processing power to be used for analytics purposes.

See More: Is Your Organization Ready to Secure Your Cloud Operations?

While a remote video surveillance system with cloud analytics capabilities can be helpful across many industries, the technology is especially valuable within construction, where there is such a strong emphasis placed on health and safety. In particular, AI and VSaaS can be used to great effect in the following areas:

One of the biggest ways in which AI and VSaaS are improving safety within the construction sector is by helping to keep construction sites secure. As a post for IIoT World explains, video analytics can be used to detect line crossing, loitering, increases in capacity, objects being taken, and a variety of other unwanted behaviors.

In situations where a construction site needs to be left unattended, a remote video surveillance system running AI analytics can detect intruders, alert site managers to items being taken, and continually monitor the construction site for other activities with no need for rest, allowing for better protection and much faster responses.

Video analytics also has the potential to identify individuals through facial recognition, and this can be used to manage access to the construction site. Regardless of whether it is during working hours or outside of them, keeping the site secure from unwanted intruders can prevent vandalism and keep workers safe.

While it is important to keep construction sites safe from intruders, it is also essential that steps are taken to minimize unwanted behaviors from construction workers too. A cloud-based video management system with AI-powered analytics can be trained to detect the presence of hard hats and flag situations where workers are not wearing them.

Beyond this, video analytics can be used to detect risky behaviors during the construction process itself. This can highlight dangerous acts or mistakes that might end up costly in the long term, but it can also help to prevent issues where the actual quality of the construction work may put people in jeopardy.

In the past, surveillance footage has been viewed after the fact. Yet, the rise of VSaaS and video analytics technology means that risky behavior can be detected in real-time, and site managers can take swift or even preventative action.

Modern VSaaS offerings still provide the conventional benefits of a surveillance system, such as the deterrent effect and the ability to provide evidence in the event of theft or vandalism, but these newer systems also provide some additional noteworthy benefits. For instance, actually identifying perpetrators becomes easier because cloud storage expands data limits, meaning footage can be recorded in 4K quality using multiple surveillance cameras.

In the event that an accident happens on a construction site, facial recognition technology can help to provide a better understanding of precisely what happened, who was involved, and what the response was.

As an article from Health & Safety Matters highlights, it is also common for construction workers to attend work while injured or experiencing ill health, and this is a growing problem that can have severe long-term consequences. Analytics can help to detect the presence of injuries or illnesses so that workers can be managed appropriately.

Construction workers face serious risks in their day-to-day lives, and firms employing these workers must take the right steps to keep them as safe as possible. Fortunately, VSaaS, AI, and cloud technology are helping to modernize on-site surveillance, allowing for real-time responses to unwanted behaviors and significant events.

How are you using AI and VSaaS to enhance your stance on safety and security? Share with us on Facebook, Twitter, and LinkedIn.

Image Source: Shutterstock

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How AI and VSaaS are Improving Safety in the Construction Sector - Spiceworks News and Insights

Every year at Adobe Max, Adobe shows off what it calls Sneaks, R&D projects that might or might not find their way into commercial products someday. This year is no exception, and lucky for us, we were given a preview ahead of the conference proper.

Project Clever Composites (as Adobes calling it) leverages AI for automatic image compositing. To be more specific, it automatically predicts an objects scale, determining where the best place might be to insert it in an image before normalizing the objects colors, estimating the lighting conditions and generating shadows in line with the images aesthetic.

Heres how Adobe describes it:

Image composting lets you add yourself in to make it look like you were there. Or maybe you want to create a photo of yourself camping under a starry sky but only have images of the starry sky and yourself camping during the daytime.

Im no Photoshop wizard, but Adobe tells me that compositing can be a heavily manual, tedious and time-consuming process. Normally, it involves finding a suitable image of an object or subject, carefully cutting the object or subject out of said image and editing its color, tone, scale and shadows to match its appearance with the rest of the scene into which its being pasted. Adobes prototype does away with this.

We developed a more intelligent and automated technique for image object compositing with a new compositing-aware search technology, Zhifei Zhang, an Adobe research engineer on the project, told TechCrunch via email. Our compositing-aware search technology uses multiple deep learning models and millions of data points to determine semantic segmentation, compositing-aware search, scale-location prediction for object compositing, color and tone harmonization, lighting estimation, shadow generation and others.

Image Credits: Adobe

According to Zhang, each of the models powering the image-compositing system is trained independently for a specific task, like searching for objects consistent with a given image in terms of geometry and semantics. The system also leverages a separate, AI-based auto-compositing pipeline that takes care of predicting an objects scale and location for compositing, tone normalization, lighting condition estimation and synthesizing shadows.

The result is a workflow that allows users to composite objects with just a few clicks, Zhang claims.

Achieving automatic object compositing is challenging, as there are several components of the process that need to be composed. Our technology serves as the glue as it allows all these components to work together, Zhang said.

As with all Sneaks, the system could forever remain a tech demo. But Zhang, who believes itd make a great addition to Photoshop and Lightroom, says work is already underway on an improved version that supports compositing 3D objects, not just 2D.

We aim to make this common but difficult task of achieving realistic and clever composites for 2D and 3D completely drag-and-drop, Zhang said. This will be a game-changer for image compositing, as it makes it easier for those who work on image design and editing to create realistic images since they will now be able to search for an object to add, carefully cut out that object and edit the color, tone or scale of it with just a few clicks.

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Adobes AI prototype pastes objects into photos while adding realistic lighting and shadows - TechCrunch

Yuichiro Chino | Moment | Getty Images

Businesses and consumers have been grappling with supply chain issues for months, resulting in annoying shortages of all kinds of products, including all-important semiconductor chips.

And while the CHIPS and Science Act, signed into law in August, is designed to boost semiconductor manufacturing in the U.S., there's no telling what effect the legislation will have on supply, or even when.

"The semiconductor supply chain is still constrained," said Brandon Kulik, semiconductor industry leader and principal at Deloitte Consulting. "Lead times on average have come down slightly, given softening in the consumer electronics segment [laptops and smartphones], and demand for memory has declined. But demand for higher performing data center chips, defense, and automotive chips remains historically high, with some semiconductor companies seeing growth in the area of 40% or more."

One potential nearer-term solution for companies that rely on semiconductors: advanced data analytics and artificial intelligence tools to help manage supply issues.

"The Covid-19 pandemic vividly illustrated the impact that unexpected events can have on global supply chains," said Rohit Tandon, managing director and global AI & analytics services leader at Deloitte. "However, AI can help the world avoid similar disruptions in the future."

By crunching through the massive amounts of data being generated by today's supply chains, AI can predict a range of unexpected events, such as weather conductions, transportation bottlenecks, and labor strikes, helping to anticipate problems and reroute shipments around them, Tandon said.

"AI can also enable dramatic improvements in other key supply chain areas, including demand forecasting, risk planning, supplier management, customer management, logistics, and warehousing," Tandon said.

This can lead to improved operating efficiency and working capital management, greater transparency and accountability, and more accurate delivery estimates; and fewer supply disruptions, Tandon said. "In addition, manufacturers that are using AI for visibility in their smart factory operations can better respond to potential disruptions to avoid delays and pivot if needed, enabling them to be more resilient while continuing to meet customer demands," he said.

"Organizations can leverage data analytics tools for deeper insights across the supply chain," Tandon said. "These tools are designed to improve demand prediction and support data sharing with customers and partners." In addition, organizations can use AI to predict or forecast supply chain-related events such as logistics challenges, geopolitical issues, and supply disruptions.

They can either execute actions autonomously or recommend actions stakeholders should take, "ultimately helping companies build resilience into their supply chains," Tandon said.

When deploying these tools for supply chain management, it's a good idea to start with a small and narrow scope and evolve the depth and breadth of the models and algorithms as the results show their accuracy and value, Tandon said.

High-quality data is also important. "Underlying data is key, as bad data equals bad analytics," Tandon said."Lack of transparency across the supply chain is often the result of inconsistent and incomplete data across product, supplier and customer.Standing up data governance processes that align to common definitions and [fixing] data issues provides the foundation of data quality that builds trust in the output of the analytics and AI process."

Rand Technology, an independent semiconductor distributor, is using data analytics to solve customer challenges related to supply.

"For example, if a customer has a need to alleviate inventory surplus, we use data and analytics to identify other users of these products and create an opportunity to rehome them," said Jennifer Strawn, vice president of solutions and sourcing for the Americas and EMEA at Rand. "In this way, OEMs and contract manufacturers are able to shore up their inventory mix of components."

In addition, data and analytics are especially important during a manufacturer's new product introduction phase in the bill of materials selection, Strawn said. "It is critical, during this phase, to identify where you can build flexibility into the design so that there are multiple sources for semiconductors on the approved list of materials," she said.

In this way, manufacturers are not reliant on a single semiconductor provider, which in the current environment could impact business. "We leverage advanced analytics to help determine the availability of these semiconductors and to spot trends and patterns, such as gaps, price increases or product change notices, before products are in production," Strawn said. Rand also uses the technology to drive decisions on future scenarios and to determine how much buffer stock a company might want to secure, she said.

Rand also uses advanced data analytics to identify trends and patterns that enable it to guide customers strategically through perilous market conditions. "With modeling and real-time visibility into availability, market shifts and conditions globally," Strawn said, "we are able to help reduce risks and map strategies in advance that can be employed when we note certain changes and disruptions in the industry."

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How using analytics and AI can help companies manage the semiconductor supply chain - CNBC

Hospitals and health systems are largely using artificial intelligence for purposes like patient scheduling and disease prediction, several digital and data executives told Becker's.

That lines up with findings of an Oct. 18 Deloitte report on the state of AI, which found the top healthcare applications include customer service operations and computer-assisted diagnostics.

At Winston-Salem, N.C.-based Novant Health, for example, is using AI to optimize scheduling and cut down on patient wait times. The health system also employs AI for its hospital-at-home program and other remote monitoring efforts.

"By combining our diagnostics, predictive health scoring, as well as vitals management, we are looking for being able to move as much to avenues that will provide the patient with a more comfortable and familiar environment," said Karl Hightower, chief data officer and senior vice president of data products and services of Novant Health.

According to the Deloitte report, the top AI uses for patient experience and marketing were customer service operations and image recognition/digital radiology (tie, 41 percent); computer-assisted diagnostics (40 percent); personalization and patient vitals monitoring (tie, 38 percent); and omnichannel experience management (35 percent). The consulting firm surveyed 260 global healthcare and life science organizations from across the globe.

"The leading industry-specific healthcare AI use cases focus on outcomes and monitoring in such potentially transformational areas as AI-assisted diagnoses including predictive diagnoses, patient engagement, insurance fraud detection and smarter hospitals," the report stated.

The data and digital health leaders interviewed by Becker's found these categories to be largely representative of their uses of AI.

"Mayo Clinic has AI projects that fall under the diagnostics, customer service, and patient vitals monitoring categories, but we also have many AI initiatives that would be considered operational, or administrative, uses," said Ajai Sehgal, chief data and analytics officer of the Rochester, Minn.-based health system.

Those include patient volume prediction, resource allocation, and billing. At Mayo's Center for Digital Health, most use cases involve natural language processing, taking spoken word or text and turning it into a structured format.

Mayo Clinic's digital front door app has a natural language processor to match a patient's primary concern to the health system's scheduling tree to expedite new appointments.

New York City-based NewYork-Presbyterian Hospital has deployed such tools as predictive machine learning, robotic process automation and AI imaging.

"Particularly, over the course of the last several years, and because of the COVID-19 pandemic, we've heavily leveraged AI within our customer service operations," said Peter Fleischut, MD, senior vice president and chief transformation officer of NewYork-Presbyterian.

Its NYP Connect App offers self-scheduling, EHR access and telehealth visits. Patient-facing calls are automated through scheduling and conversational AI.

Most of the AI efforts at Duarte, Calif.-based City of Hope fall under clinical decision support, a combination of computer-assisted diagnostics, vital sign monitoring and risk detection, said Chief Digital Officer Mark Hulse.

City of Hopes combines AI, genomics and other clinical data to predict the risk of sepsis for transplant patients, 30-day unplanned readmissions, surgical complications, and survival and early disease. AI also helps forecast financial metrics and patient readiness for early discharge.

At Sioux Falls, S.D.-based Sanford Health, the enterprise data analytics team has developed algorithms to try to predict which patients might be at risk of Type 2 diabetes or which women should have mammograms earlier than recommended.

"We are applying predictive models and risk stratification to our electronic medical record that consider and review all aspects of patients' histories to inform clinical decision-making," said Doug Nowak, vice president of enterprise data analytics for Sanford Health.

Jacksonville, Fla.-based Baptist Health works with AI to cut back on repetitive tasks for employees and optimize operating room scheduling.

"My prediction is that as data is shared more widely, coupled with significant increases in computational ability, and we turn towards utilization of quantum computing for big data analysis, AI will truly be unlocked with numerous more categories and hard return-on-investment use cases," said Aaron Miri, Baptist Health's senior vice president and chief digital and information officer.

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Where health systems are spending their AI dollars - Becker's Hospital Review

New AI image-generation systems make headlines every day but that revolution started many years ago. Now one of the most established services for AI face generation has expanded its offering to include full body images. An early use of computer-made faces was for news stories, video games, and documentaries when a person was needed to convey an idea or represent an unknown individual for which no photo was available. Keeping a stock library of faces isnt too difficult for an agency but standing poses are harder since the type of clothing affects the possible uses of the images. In the past, one or more models would need to be hired for these types of shots.

Generated Media, the company behind the Generated Photos website and its free, real-time Face Generatorrecently launched a massive library containing 100,000 AI human images that look like real people, wearing a variety of clothes and standing in relaxed-looking poses with neutral facial expressions.

There is some concern about how the rapid advancement of artificial intelligence will affect various industries and it seems artists, actors, and models arent even safe from computer technology. When you see a person in an advertisement or shopping website, are they even real? It might be hard to tell. Whats clear is this revolution will continue to accelerate until everyone will either be working with computers or replaced by machines.

Generated Photos AI-created humans are still in development and the full set must be downloaded in a 1.3GB zip file in order to view individual images. Despite such a large collection, the library is limited to young, slim adults at the moment. That will be expanded, according to a representative from the company, to include different ages, body types, various poses, and custom clothes, as has been done with faces.

Eventually, a searchable database that works like the Face Generator will be available. The Generated Photos website also includes an anonymizer feature that allows you to upload a selfie and the system will find the closest match from its database of millions of faces, so you can post a photo online thats similar to your real appearance but not actually you. This and the other tools are free for personal use and can be licensed for commercial use.

The industrial revolution saw the loss of labor-intensive jobs and the AI revolution will soon be coming for creative and analytical workers. In a utopian future, all work would be the domain of machines whether taking the form of robots or operating virtually over the internet, leaving humans to lives of leisure. The tricky part will be navigating the transitionary time.

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Watch out models, the AI revolution is coming for your jobs too - Digital Trends

It's absolutely mind-blowing how much artificial intelligence has come to play a central role in photography. There's the presence of it in everyday usage in smartphones, with things like portrait mode and night sight, but now, even more powerful tools are available to desktop retouchers. Just check out how it works on this 70-year-old photo.

Coming at you from Glyn Dewis is a video that incorporates a bunch of different tools in the service of restoring a damaged 70-year-old family photo of his. While ordinarily, this would be a quick retouch job to remove scratches and tears, in this particular case, Dewis wanted to be able to not only do that, but increase the resolution and make it an aspect ratio that would work for an 8x10" print as well.

The first tool Dewis uses should be pretty familiar to most photographers, and that's one of Adobe Photoshop's neural filters, the photo restoration filter, which does a decent job of most basic cleanup functions. As he points out, there are some other functions there to colorize photos, but for this video, he sticks to black and white.

The mind-blowing part came in how Dewis changed the aspect ratio of the photo. Using a tool called DALL-E 2, which describes itself as "a new AI system that can create realistic images and art from a description in natural language." Dewis was able to pop his photo into the system and have the AI fill in the missing background details quite convincingly, such that he now had enough headroom to crop into the aspect ratio he wanted.

I got so wrapped up in how this tool works. It's not perfect by any stretch of the imagination, but Dewis' use case is an interesting one for photographers.

The last step is a piece of software that's not as esoteric as DALL-E, and that's Topaz Gigapixel AI, an image upscaler that can increase the size of an image by 600%, since DALL-E is a bit limited in its output resolution.

With those three tools, Dewis was able to retouch his old photo with much less effort than it would have taken in the past.

What do you think of the results?

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Using AI to Restore Old Photos Actually Works - Fstoppers

Symbl.ai Enhance Conversation Intelligence Accessibility With Managed Libraries and Recommendations

SEATTLE (PRWEB) October 19, 2022

Symbl.ai, a developer-first platform providing best-in-class conversation intelligence (CI), has announced two new breakthrough features designed to make the technology more accessible for developers with little to no expertise in conversation AI or machine learning.

Symbls CI platform allows users to track a wide array of actionable insights from conversations, both in real-time and asynchronously. These insights include topics of discussion, questions raised, action points, as well as tone, sentiment and intent, all of which can be used to provide automatic summaries of conversations, score leads, train staff and more.

Users can define their own groups of keywords and phrases with similar meanings known as trackers, which the technology then uses to provide actionable insights. Previously, the onus was on businesses themselves to create and grow their library of trackers, resulting in a cold start problem for those with limited resources or experience. To grow its tracker library, a company would need to invest a great deal of time watching, listening or reading through conversations to grow their tracker library manually, resulting in missed tracker opportunities and slow time to market.

Symbl.ai has now rolled out a verticalized managed libraries feature which eliminates the cold start problem and allows businesses to start using CI functionality out of the box with a predetermined and constantly updated library of trackers. Companies can select a library that best suits their industry and get started immediately, adding their own tracker groups in just a few clicks.

A new personalized recommendations feature has also been introduced which uses Symbl.ai technology to identify new tracker opportunities as they emerge and notify users. Recommended trackers can be added seamlessly, allowing businesses to grow their tracker libraries intelligently from the outset without the need for manual input.

When we first launched Trackers, customers were excited to use the functionality because it provided them with the flexibility to track insights appropriate for their specific use cases, commented Surbhi Rathore CEO, Symbl.ai. However, we quickly realized that some customers were struggling to get started with tracker functionality, primarily because they had to develop their own library of trackers to get the most out of the feature. We listened to their feedback and are now launching the managed trackers library and recommendations features to give customers a running start and allow them to generate actionable insights from the outset.

To take advantage of trackers and recommendations, users simply need to login to the Symbl.ai platform and select the trackers most appropriate to their industry or use-case. Next, users can process conversations from the platform and view the results of managed trackers to see how they are performing. Managed trackers can be customized to include more phrases specific to a given business or product. As conversations are processed, live recommendations will appear based on conversations that have been recorded in the past 30 days. If a user accepts a recommendation, it will be seamlessly integrated into their existing tracker library.

To learn more about managed trackers and proactive tracker recommendations, users can access the documentation and FAQs here.

About Symbl.aiSymbl.ai is a Conversation Intelligence (CI) platform to rapidly deploy real-time conversation understanding at scale on any communication channel. Our comprehensive suite of APIs unlock proprietary machine learning to generate summarization, track intents, actionable insights, sentiments, and knowledge contextually across audio, video, or text conversation data. For more information, visit https://symbl.ai/. Follow us on social media: Follow us on social media:https://www.linkedin.com/company/symblai/Linkedin,Twitter,Instagram,https://www.facebook.com/symbldotai/Facebook,https://www.youtube.com/channel/UCpqOyNdFI0kASCZL-eCnkcAYouTube,https://github.com/symblaiGithub

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Symbl.ai Enhance Conversation Intelligence Accessibility With Managed Libraries and Recommendations - PR Web