The post ABBYY’s 2nd Annual Intelligent Automation Month Showcases AI’s Power to Speed Up Business appeared first on AiThority.

GroupBy Inc., a leading provider of AI-first Search and Product Discovery solutions for B2C and B2B retail, today unveiled Enrich AI, a cutting-edge product data enrichment platform designed to revolutionize product information management. Leveraging sophisticated generative AI algorithms and GroupBy’s years of deep retail expertise, Enrich AI empowers retailers to create rich shopping experiences with enhanced product data – driving substantial revenue growth. “Enrich AI represents a quantum leap in data enrichment and product data management,” stated Roland Gossage, CEO at GroupBy. “By seamlessly integrating advanced AI with our deep domain expertise in retail, we are delivering a solution that addresses the critical challenges retailers face in managing and optimizing their product data. This sophisticated self-serve platform enables B2C and B2B retailers to achieve unprecedented levels of data accuracy, consistency, and completeness, ultimately optimizing search relevance, merchandising effectiveness, and overall business performance.”

Also Read: AiThority Interview with Kunal Purohit, President – Next Gen Services, Tech Mahindra

“Enrich AI represents a quantum leap in data enrichment and product data management”

Enrich AI harnesses the power of AI to revolutionize product data management. By automating complex data enrichment tasks, Enrich AI accurately extracts, standardizes, and enriches product data based on attributes, descriptions, and images at scale. This streamlined process minimizes costly errors, accelerates time-to-market, and frees up valuable resources for strategic initiatives, while making it easier for retailers to manage their catalogs.

Moreover, Enrich AI leverages GroupBy’s extensive proprietary Global Taxonomy Library to ensure consistent and accurate product categorization. By applying a robust, industry-specific taxonomy, developed by GroupBy’s breadth and years of experience working with various retail verticals, retailers can enhance product discoverability, improve search relevance, and optimize merchandising efforts. This granular level of product classification empowers retailers to deliver highly targeted attributes and values for product recommendations and personalized shopping experiences.

To further enhance data reliability and integrity, Enrich AI employs advanced algorithms to detect and correct errors, inconsistencies, and missing information within product data. By improving data quality, retailers can reduce costly returns, enhance customer satisfaction, and build trust in their brand.

Ultimately, by optimizing product discoverability and driving business growth, Enrich AI enables retailers to improve the quality of their data, personalize customer experiences, and increase customer satisfaction. With enriched product data, retailers can unlock new revenue streams, gain a competitive advantage, and thrive in today’s dynamic retail landscape.

Also Read: AiThority Interview with Seema Verma, EVP and GM, Oracle Health and Life Sciences

Key technical features of Enrich AI include:

• Advanced AI Algorithms: Utilize state-of-the-art generative AI models for accurate and efficient data enrichment.
• Product Attribute Intelligence: Fast and efficient attribute enrichment from product image and text data in a single step.
• Deep Retail Expertise: Built on a foundation of industry knowledge and best practices across retail verticals.
• Taxonomy Enrichment: Manage taxonomies tailored to specific product categories based on business needs.
• Product Catalog Management: Automated management of catalogs to maintain enrichment for products that churn.
• Robust PIM/PXM Integration: Seamlessly integrate with existing product information management systems.
• Quality Assurance: Automated data quality checks ensure data accuracy and consistency through continuous monitoring and validation.
• Product Transformations: Involve humans in the loop to quickly curate and edit product values across the catalog.
• User-Friendly Interface: Empower users with intuitive tools for easy data management and enrichment.
• Simplified Integration: Seamlessly access Enrich AI functionality directly from the GroupBy Command Center, eliminating the need for manual data injection and streamlining the enrichment process.
• Expert support: Access professional services for seamless catalog implementation and data enrichment aligned with the proprietary Global Taxonomy Library.

By combining AI-powered precision with GroupBy’s deep retail expertise, Enrich AI delivers unparalleled product data enrichment capabilities. Retailers can now unlock the full potential of their product data, gain a competitive edge, and drive long-term business success.

Also Read: AiThority Interview with Yair Amsterdam, CEO of Verbit 

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post GroupBy Launches Enrich AI: Revolutionizing Product Data Attribution with Advanced AI and Proprietary Global Taxonomy appeared first on AiThority.

New r1 orders globally are now shipping within three business days

Today, AI startup rabbit inc. announced that r1, a first-of-its-kind AI-native device that puts easy access to the industry’s most advanced consumer AI models in your pocket, is now available across the European Union and the United Kingdom. In addition, rabbit announced that a****** r1 orders globally will ship within three business days.

r1 is rabbit’s first hardware product and has made waves in the consumer electronics industry as the best-selling and most-used native AI device to-date, with more than 100,000 devices sold. One-third of r1 devices sold to-date have been purchased in Europe. Customers have discovered a wide variety of helpful use cases to improve their daily lives with AI, from deciphering complicated parking and road signs, and getting important gardening tips using the AI-powered rabbit eye camera, to translating conversations in real-time and generating healthy recipe ideas with access to leading large language models (LLMs).

Also Read: AiThority Interview with Seema Verma, EVP and GM, Oracle Health and Life Sciences

r1, rabbit OS and rabbithole – a personalized AI agent experience from end to end

Running on a personalized operating system, r1 is the only consumer AI device that gives users quick and affordable access to the leading AI models in one device, including LLMs from ChatGPT, Perplexity, and Anthropic. Combining custom-built software with sleek hardware designed in collaboration with renowned design firm Teenage Engineering, r1 is an on-the-go curiosity catcher, a journal you write with your voice, an encyclopedia at your fingertips, a recorder that summarizes your every thought, a pocket translator, and a reason to bring friends and family together. Each user can manage their personalized history and supported online services in rabbithole, the accompanying secure cloud hub and “brain” of the user’s personal AI assistant. Take a look at our use cases to learn more about how r1 offers a new and useful AI-native experience.

Commitment to constant improvement for a better user experience

Since launching r1, rabbit has demonstrated its community-focused approach to ensure a fast feedback loop between its consumers and engineers, continuously and rapidly improving and adding more value to r1 through regular software updates based on user feedback. The new “beta rabbit” feature, introduced in July, enables r1 to provide significantly smarter answers to more complex queries. A number of other key updates have also made r1 more useful and delightful, including global memory recall, which personalizes responses in relation to a user’s rabbithole journal content; Wolfram|Alpha integration, which provides users with increased accuracy in computational queries related to mathematics, science, technology, society, and culture; and Magic Camera, which turns photos taken by r1 into creative AI-generated images. While there are currently some regional limitations in Europe, including availability of certain connected apps and additional operating languages, the product is vastly more capable than it was at launch, with new improvements and features added through regular over-the-air (OTA) and cloud updates. This cadence will also apply to Europe as the team continues to listen to feedback and rapidly apply it to the user experience.

“r1 was designed from day one to be a global device, and we want to deliver it to every corner of the world,” said Jesse Lyu, Founder and CEO of rabbit. “We’re very encouraged to see the existing appetite for r1 in Europe already as we pave the way in this new category of AI-native products.”

Built around security from day 1 and constantly becoming stronger

rabbit designed the architecture of rabbit OS with security and privacy at the core. “The most important thing we do at rabbit is earn and protect customer trust. This is something that everyone, not just the security team, is charged with when they join the company,” said Matt Domko, Head of Security at rabbit. “We’re actively taking steps to consistently improve our security program on a daily basis.”

Also Read: AiThority Interview with Kunal Purohit, President – Next Gen Services, Tech Mahindra

To keep up with the fast pace of rabbit’s software updates and growing set of consumer use cases, rabbit regularly works with credible third-party security partners to test the resilience of its system and ensure consumers’ privacy and information security are effectively protected. Learn more about the company’s recent penetration test in this blog post.

r1 only listens when the user presses the physical push-to-talk button to interact with the device, and its rotating camera defaults to a position that physically blocks the lens unless the user explicitly requests it. rabbit also implemented a vulnerability disclosure program (VDP) in May to encourage researchers, developers, and the general public to submit vulnerabilities in a responsible manner.

rabbit r1 is available today across the entire European Union (excluding Malta) and can be purchased at www.rabbit.tech. It costs $199 with no subscription necessary; please refer to the website for current local prices in the UK and Europe. New orders globally will also be processed and shipped within three business days.

Also Read: AiThority Interview with Yair Amsterdam, CEO of Verbit 

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post rabbit r1, the AI-native Pocket Companion, Expands Availability Across the UK and EU appeared first on AiThority.

CloudOffix, a trailblazer in Low-Code Total Experience Platforms, is excited to announce the launch of its latest AI-powered features.

CloudOffix, a trailblazer in Low-Code Total Experience Platforms, is excited to announce the launch of its latest AI-powered features. These innovations are set to redefine how businesses operate, delivering enhanced efficiency, superior customer experiences, and intelligent automation across various functions.

Also Read: AiThority Interview with Kunal Purohit, President – Next Gen Services, Tech Mahindra

“Our latest AI features mark a visionary leap forward in integrating artificial intelligence into core business functions,” said Gokhan Erdoğdu, CEO of CloudOffix. “These enhancements deliver unparalleled efficiency, accuracy, and personalization, empowering our clients to excel in today’s dynamic market environment.”

Key Advantages of CloudOffix’s AI Enhancements:

-Operational Efficiency: Automate routine tasks, reduce response times, and boost productivity.
-Precision in Communication: AI-driven tools ensure business communications are professional, accurate, and polished.
-Scalable Solutions: Flexible AI capabilities that grow with your business, adapting to new challenges and opportunities.
-Enhanced Customer Experiences: Deliver personalized interactions that cater to customer needs and exceed expectations.

A Smarter, Centralized Approach to Business Intelligence

Not all AI is created equal. Total AI—CloudOffix’s revolutionary approach that sets a new benchmark for smarter, more accurate AI by centralizing data and integrating it across various front-office processes. CloudOffix is pioneering this innovative technology to transform how businesses operate, innovate, and succeed.

Total AI seamlessly brings together data and functionalities from multiple business units, including sales, CRM, HR, marketing, project management, invoicing, and more. This comprehensive integration ensures a smooth and cohesive data flow across the entire organization, breaking down silos and enabling more informed decision-making.

By leveraging AI to analyze vast amounts of data from diverse sources, Total AI empowers businesses to make more informed decisions across key areas such as sales forecasting, personalized marketing, and operational efficiency. This data-driven approach ensures that decisions are not just timely but also highly accurate and impactful.

Total AI plays a pivotal role in understanding customer behavior and preferences, enabling businesses to tailor their offerings and interactions to meet individual needs, ultimately enhancing the customer experience. Additionally, it optimizes employee experiences by streamlining HR processes, identifying the best-fit candidates, and providing personalized training and development, thereby improving satisfaction and productivity.

With AI-driven tools, Total AI enhances digital interactions, making them more intuitive and efficient. Whether through AI-powered chatbots or advanced analytics, businesses can better understand user behavior and deliver seamless, responsive user experiences that drive satisfaction and engagement.

Also Read: AiThority Interview with Seema Verma, EVP and GM, Oracle Health and Life Sciences

Why Centralized Data Matters

The effectiveness of AI hinges on the quality and comprehensiveness of its training data. In many organizations, data is fragmented across departments, resulting in incomplete or inconsistent datasets. Total AI solves this problem by centralizing data from all front-office processes within a single platform.

By consolidating data from sales, marketing, customer support, and HR, Total AI creates a comprehensive, 360-degree view of the business. This unified data structure allows AI to draw connections and uncover insights that would otherwise remain hidden in isolated datasets, resulting in more intelligent AI that can generate highly accurate predictions and recommendations.

How Total AI Enhances AI IQ

Rich, Diverse Data Sources: Access to data from multiple departments allows Total AI to analyze a broader array of variables and scenarios, enriching the AI’s learning process and improving its adaptability and accuracy.

-Contextual Understanding: Centralized data enables Total AI to understand the context behind each data point. For example, a sales figure isn’t just a number; it’s part of a broader narrative that includes customer interactions, marketing campaigns, and HR efforts. This contextual understanding leads to more nuanced and insightful analysis.

-Real-Time Updates: Total AI ensures that data is continuously updated in real-time, so AI models are always working with the most current information, providing timely and relevant insights.

-Cross-Department Collaboration: By integrating data across departments, Total AI fosters collaboration and alignment within the organization. AI-driven insights can be shared across teams, leading to more cohesive strategies and better decision-making.

CloudOffix’s integrated approach amplifies our AI capabilities to deliver smarter, more actionable insights. With CloudOffix Total AI, the possibilities for what you can achieve with artificial intelligence are truly limitless.

Also Read: AiThority Interview with Yair Amsterdam, CEO of Verbit 

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post CloudOffix Unveils Groundbreaking AI Features in Low-Code Total Experience Platform appeared first on AiThority.

The integration of artificial intelligence (AI) in wound care shows promise of transforming the field, enabling more precise diagnostics, personalized treatment plans, and significantly improved healing outcomes. Providers face many challenges, including time constraints, regulatory demands, and electronic health record (EHR) input. Though progress has been made, information sharing across colleagues and departments has continued to be a barrier to optimal care delivery, and without the correct data available, informed clinical decisions cannot be made. Considering these factors, the wound care industry requires technological advancements to help alleviate common hurdles and enhance care delivery and the patient experience. AI has the opportunity to play a role in this movement, but wound care is experiencing parallel adoption challenges with other healthcare sectors as technology progresses. Grandview Research estimates that the global wound care market will increase at a compound annual growth rate of 4.17% between 2024 and 2030, justifying the need to expand technology capabilities in this sector. Additionally, the aging population is causing an increase in patients with chronic health issues, further driving the need for more advanced care methods.

Also Read: AI Inspired Series by AiThority.com: Featuring Bradley Jenkins, Intel’s EMEA lead for AI PC & ISV strategies

Effective wound care requires careful attention and an in-depth understanding of the numerous factors that can influence healing. By incorporating AI in wound care technology to expand knowledge bases and gather insights, providers may be able to better identify needs to address challenges and provide the best treatment options. The use of AI could enable providers to minimize guesswork and deliver more targeted treatments to increase recovery success. Advancements in wound care technology can transform care delivery and streamline clinical operations, creating a new standard for care in the industry.

Expanding wound care treatment options

As an industry that has lacked robust options for treatment, especially for more complex wounds, ensuring accuracy and personalization for individual patients is a crucial step in implementing modern technology. From the start, an accurate diagnosis can make or break the subsequent steps and outcomes of a patient’s treatment plan. AI shows potential to play an influential role in wound care, from measurement and analysis to assisted clinical decision-making for treatment plans. For example, AI algorithms could reference previous patients’ data to identify wound types and stages, increasing accuracy and improving treatment planning. Wound measurement is another essential component of this identification process. Conventional ruler-based measurement practices have a  44% error rate, but AI imaging and measurement can significantly reduce this statistic by measuring a wound accurately through automated digital planimetry. With more accurate measurements, courses of action and outcomes may look drastically different.

More personalized treatment plans are another potential benefit of AI integration in wound care. Utilizing AI to analyze an individual patient’s electronic health record data, providers could take more tailored steps to ensure the best chances of recovery. They may also be able to reference a wider range of data to determine the next best course of action, such as dressings and medications to prescribe as the wound heals.

AI may also be able to offer enhanced monitoring and feedback on treatment plans and progress. With the availability of wound monitoring applications and devices, real-time data collection and analysis can enable ongoing treatment adjustments. In the U.S., approximately 2.5 million individuals develop a pressure injury in acute care facilities every year. AI integration could help reduce the number and severity of hospital-acquired pressure injuries (HAPIs) and prevent needless amputations due to diabetic ulcers by assisting with monitoring, especially in understaffed facilities. The average HAPI costs a hospital up to  $70,000 per case, and HAPIs are the second most common hospital lawsuit claim after wrongful death. For diabetic ulcers, with the rate of diabetes increasing, especially among younger and disadvantaged populations, the rate of amputations has increased over the past several years, further representing the demand for AI’s assistance in addressing chronic wound conditions.

Also Read: Extreme Networks and Intel Join Forces to Drive AI-Centric Product Innovation

Improved quality of life and long-term outcomes

Positive outcomes are always the goal at the end of a treatment plan. A patient’s quality of life in both the short and long term could be improved with the use of AI through reduced healing time, minimized complications, and improved patient engagement and compliance. AI-driven care can potentially accelerate healing by using accurate insights to inform care decisions, but more research needs to be done to validate the impact of AI in improving clinical outcomes. Predictive analytics may help spot potential problems early on and help avoid infections or other wound-related issues. For chronic wounds that take more time to heal, AI’s ongoing role in the care plan and process could be pivotal to improving patient outcomes.

AI and its accompanying tools may also drastically increase patient engagement and compliance. With solutions now available to support patient education and engagement, individuals can be more involved in their care journeys with expanded knowledge of their condition and treatment plan. Patient engagement is increasingly recognized as an integral part of health care and a critical component of safe, people-centered services. Informed patients are more likely to feel confident enough to report positive and negative experiences and have increased compliance with established care management plans.

Also Read: More than 500 AI Models Run Optimized on Intel Core Ultra Processors

 Enhancing clinical workflow

Aside from patient-centric benefits, provider organizations can also benefit from implementing AI solutions into their practices. A more streamlined workflow is a primary benefit of integrating AI into practices because it can automate routine tasks. In November 2023, 56% of nurses reported burnout, so finding ways to reduce tedious administrative tasks and allow clinicians to focus on care delivery and patient engagement can help better maintain or even improve the health care workforce. Clinician time is valuable, so allocating resources correctly is essential to a provider organization’s success.

AI has the potential to be a catalyst for the transformation of wound care and beyond. Showing promise of enabling more informed care delivery with transparency and efficiency will positively impact wound care treatment, patient outcomes, and clinical processes that can propel this sector into the future. While hesitancy remains around the adoption of AI in health care, the positives almost certainly outweigh the risks. Engaging with AI technology will help set clinical practices up for success in care delivery and operations, but most importantly, open new doors for patients in need of treatment.

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post AI-Powered Wound Care: Enhancing Accuracy and Efficiency appeared first on AiThority.

The post SoundHound AI Acquires Amelia, Expanding Across Industries appeared first on AiThority.

With a model that blocks 97% of harmful prompts, has 95% decision accuracy, and identifies 92% of blocked prompts as potential threats, CalypsoAI leads the industry in mitigating AI risks

CalypsoAI, the leader in AI security, unveiled today at Black Hat USA 2024 that users now have access to a suite of new, industry-leading functionalities allowing them to customize their generative AI (GenAI) security measures based on what makes the most sense for their business. From rapid updates that address evolving threats in real time to new integrations and partnerships, these latest enhancements build on CalypsoAI’s cutting-edge platform and continue to deliver on its mission to secure GenAI across the enterprise—regardless of industry, model, or use case—by offering the best solution on the market.

Also Read: Humanoid Robots And Their Potential Impact On the Future of Work

“The threat landscape when it comes to AI is evolving so quickly, we realized we needed to fight fire with fire—which is exactly where our customizable scanner technology comes in”

According to research from CalypsoAI and the Everest Group, data security and privacy are among CIOs’ top concerns when it comes to generative AI, with 55% revealing it as a challenge to adoption. A significant part of this concern stems from the fact that use cases across industries, companies, and departments vary drastically. Most guardrail-like defenses are built with legacy techniques or simply not enterprise-ready, limiting effectiveness and resulting in outdated protection almost instantly. These limitations pose a significant challenge for organizations seeking to deploy and adopt GenAI while ensuring AI security can adapt to constantly evolving threats.

At the RSA Conference in May, CalypsoAI introduced its customizable GenAI Scanners, solving these major security challenges and setting a new industry standard. This game-changing technology allows organizations to create their own AI-powered scanners with simple descriptions, which CalypsoAI’s advanced LLM then transforms into a sophisticated data shield. This enables companies to address specific vulnerabilities and set detailed policies that drive the highest levels of performance. With real-time threat updates and instant adaptation, CalypsoAI is the first and only solution using GenAI to secure all enterprise use cases.

Building on this innovation, CalypsoAI’s platform offers the most advanced tools to secure, audit, and monitor internal and external GenAI usage across all models, vendors, and modes. These enhancements transcend enterprise protection across GenAI deployments more than any other solution, including:

Also Read: Humanoid Robots And Their Potential Impact On the Future of Work

• Out-of-the-Box Scanners: While many companies want to customize scanners to suit their business needs, others want the ease of flipping a switch to power protection. To meet this need, CalypsoAI offers out-of-the-box scanners that address particular business use cases and verticals, such as PII and source code vulnerability. These pre-packaged scanners round out the existing suite of fully bespoke GenAI Scanners, enabling organizations of all sizes and industries to have the security capabilities at their disposal that make the most sense for their business.
• Dynamic, Real-Time Threat Updates: The CalypsoAI Platform now has the ability to push out updates and react in real time to tackle new and evolving threats, such as zero-day attacks. This is made possible through CalypsoAI’s proprietary process which powers its advanced model to adapt seamlessly to new threats, ensuring a company’s security remains up-to-date and resilient against ever-changing cyber challenges.
• New Model Partners and Integrations: CalypsoAI recently announced a partnership with IBM watsonx to offer a comprehensive defense against modern cyber threats—blending IBM’s powerful AI models with CalypsoAI’s advanced threat detection mechanisms and proactive defense strategies.
• The CalypsoAI Security Community: CalypsoAI is creating the ability for users to share successful custom-built scanners with others—from partners in their organization’s network, colleagues, or those they interact with on channels like X or LinkedIn—to leverage to their advantage. Fundamental to the community is the desire to strengthen knowledge-sharing among security professionals and increase awareness of best practices in the effort to secure GenAI use internally and externally.

“The threat landscape when it comes to AI is evolving so quickly, we realized we needed to fight fire with fire—which is exactly where our customizable scanner technology comes in,” said Jimmy White, CTO of CalypsoAI. “At CalypsoAI we want to empower your business to proactively evolve and respond to threats before they even emerge, ensuring instantaneous, comprehensive protection and resilience. The only way to do that is to fully embrace generative AI as a key pillar and core differentiator to our platform—and the latest features ensure that we’re not only doing that at scale but giving users the ability to share those protections and learn from each other.”

CalypsoAI will be demoing the new features and its full security and enablement platform at Black Hat USA 2024. Stop by the CalypsoAI booth #4310 to see the platform come to life in an interactive crime-solving game called, ‘Behind the Mask.’ And don’t miss the company’s cocktail party on Wednesday, August 7 from 6-8 PM PDT at the Hops & Hackers Happy Hour.

Don’t miss this out: More than 500 AI Models Run Optimized on Intel Core Ultra Processors

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post CalypsoAI Builds on Success of Customizable GenAI Scanners with Multiple Product Updates appeared first on AiThority.

The post NICE Actimize Launches AI-Powered SURVEIL-X for Conduct Risk appeared first on AiThority.

Prashant Warier, Co-Founder & CEO of globally deployed healthcare AI innovator Qure.ai shares his insights into the opportunities for healthcare AI to identify disease earlier plus manage and monitor conditions to improve patient care and ultimately save lives.

The transformative power of Artificial Intelligence (AI) is making waves across all industries. Still, nowhere are the implications more profound than in healthcare. By enabling earlier disease detection, enhancing diagnostic accuracy, and optimizing treatment pathways, AI can dramatically improve patient outcomes while making quality care more accessible and equitable globally. One of healthcare AI’s most promising applications is the early detection of diseases like lung cancer. Lung cancer is the leading cause of cancer death worldwide, claiming an estimated 1.8 million lives per year. This staggering mortality is due in large part to the fact that lung cancer is often diagnosed at a late stage when treatment options are limited, and outcomes are poor. However, AI-powered tools are now able to rapidly analyze medical imaging data like chest X-rays and CT scans to spot subtle signs of earlystage lung cancer that are easy for even experienced radiologists to miss. By identifying these cases much sooner, patients can begin treatment at a point when it is far more likely to be successful, significantly improving prognosis and survival rates.

Also Read: AI For One and All

AI to detect disease early and expedite treatment planning

In the United States, the impact of such AI tools could be tremendous. Despite spending far more on healthcare than any other nation, the U.S. lags behind many other high-income countries on key health metrics like life expectancy and avoidable deaths. Much of this disparity can be attributed to delayed diagnoses and lack of timely access to appropriate care, issues that disproportionately affect underserved communities and contribute to stark health inequities. By making lung cancer screening faster, more accurate, and more widely available, AI has the potential to level the playing field, ensuring that everyone has access to lifesaving early detection regardless of their geographic location or socioeconomic status.

The benefits of AI-assisted early detection extend beyond lung cancer to many other diseases. Tuberculosis, for example, remains one of the world’s deadliest infectious killers, claiming close to 1.5 million lives per year – and cases are on the rise in the U.S., especially among vulnerable populations like the homeless, immigrants and the incarcerated. Here, too, AI can be a game-changer by rapidly triaging chest X-rays to identify likely TB cases for further testing.

When integrated into public health workflows, these tools can help catch and treat more cases earlier, stemming the spread of infection and saving countless lives. The AI models developed for TB detection are already demonstrating immense potential to strengthen health systems and improve disease control efforts globally. In high-burden countries like India, these tools are being deployed at scale to screen broad populations and connect probable cases with confirmatory testing and treatment. The ability to condense an otherwise lengthy diagnostic process into minutes has profound implications for expanding access to timely care. By reducing the cost and complexity of screening, it becomes feasible to proactively test high-risk groups even in low-resource settings, shifting the paradigm from passive to active case finding. Beyond diagnostics, AI is also poised to dramatically improve the management of acute medical emergencies like strokes.

Strokes affect someone in the U.S. every 40 seconds on average and are a leading cause of severe longterm disability. However, new AI tools can now analyze CT scans and MRIs with expert-level accuracy to quickly triage stroke and other critical brain conditions, informing treatment decisions where every second counts. This rapid risk stratification ensures that patients with emergent conditions are identified and treated without delay while reducing unnecessary transfers for non-critical cases. The result is improved outcomes, lower costs, and more efficient use of specialized neurointerventional services, which are often in short supply. The implications of these AI-powered decision-support tools for emergency medicine are profound. The ability to provide the proper care in the right place without delay can significantly reducedisparities in outcomes from acute conditions. Here, too, the impact stands to be most significant in underserved communities where access to top-tier specialists and facilities has historically been limited.

Also Read: Surviving the AI Marketing Revolution: How to Go From an Onlooker To Riding the Wave of Change

Agile, adaptable and easily accessible AI

As these examples illustrate, the power of AI to improve health outcomes and access to care is immense and multifaceted. But what is incredibly transformative about today’s healthcare AI is the fact that so many of these tools are deployable via the cloud, with the potential to bring expert-level diagnostic and prognostic insights to care settings that have long lacked access to such capabilities – from rural health clinics to community hospitals and even home-based care. With just a smartphone or laptop, clinicians can leverage the same sophisticated machine learning and computer vision algorithms driving breakthrough research at leading academic medical centers. In this way, AI is truly democratizing access to advanced care capabilities, ensuring that a person’s health outcomes are not determined by their zip code or proximity to a major urban hospital.

Democratizing access to quality healthcare

Of course, realizing the full potential of healthcare AI will require ongoing collaboration between technology developers, clinicians, policymakers, and patients. Regulatory frameworks must evolve to ensure that AI tools are safe, effective, and equitably deployed. Rigorous research will be needed to validate these technologies across diverse patient populations and care settings. Education and awareness-building will be essential to foster public trust and acceptance. Critically, AI must be implemented to empower physicians rather than replace them, augmenting their clinical decision-making capabilities while preserving the human touch essential to compassionate care.

But if we get it right, AI could be the key to ushering in a new era of healthcare – one where diseases are caught and treated sooner, therapies are optimized for each patient’s unique needs, and quality care is available to all who need it, irrespective of geographic or socioeconomic boundaries.

Far from supplanting humans, the power of AI can, in fact, scale and democratize the best of human expertise, ensuring that every patient receives the timely, personalized care they need and deserve. That is a hopeful vision of a healthier, more equitable future – and one well worth striving for.

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post How AI Is Making Healthcare More Accessible & Equitable appeared first on AiThority.

AI-powered investigation combined with behavioral detection and response reduces false positives for time-strapped detection engineers

RAD Security takes the stage as a finalist in the Black Hat Startup Spotlight Competition, it unveils the first-ever AI-powered incident investigation capability for behavioral detection and response. Today, cloud security is based almost exclusively on signature-based detections, which are notorious for burdening security teams with false positives. RAD Security is the first to combine AI-powered incident investigation with behavioral, signature-less detections, to significantly reduce false positives and provide much-needed relief for overburdened security teams.

Also Listen: AI Inspired Series by AiThority.com: Featuring Bradley Jenkins, Intel’s EMEA lead for AI PC & ISV strategies

“By definition, signatures are stateless, making investigations based on the signature-focused approach inaccurate and tedious,” says CTO and Co-Founder Jimmy Mesta. “By adding AI-powered investigations to behavioral detection, which is already a step ahead of signature-based detection in accuracy, security teams can quickly get light years ahead in the accurate assessment of incidents.”

RAD’s behavioral approach and AI-powered investigations result in the lowering of false positives on their own; but by putting these two capabilities together, RAD enables security teams to achieve a multiplier effect. The enhanced accuracy of behavioral methods versus signature-based methods is easily demonstrated using multiple examples of attack tactics like reverse shells, access to sensitive data, and a Sudo CVE. In these examples, while signatures can be easily bypassed by avoiding the exact parameters, they are detected by RAD’s behavioral solution. By the same token, a behavioral drift event is not always a malicious event, so the addition of the AI investigation capability ensures additional accuracy. AI is particularly suited for looking across large sets of data and quick contextualization, making it a natural investigation tool and engine to analyze benign versus malicious drift.

Throughout the history of cyber security, and most famously in the endpoint and network security markets, signatures have eventually been replaced by behavioral methods in response to an evolving threat landscape. Today, the cloud security category is nearly entirely composed of signature-based approaches with runtime security and Cloud Workload Protection (CWPP) that are standalone or part of a broader Cloud Native Application Protection Platform (CNAPP). In sharp contrast to signature-based CNAPPs, or posture-focused Cloud Security Posture Management (CSPM), RAD Security’s Cloud Detection and Response (CDR) solution creates behavioral baselines of unique good behavior to detect zero day attacks, enriching detections with real-time identity and infrastructure context that inform response actions.

More and more, detection and response is being accomplished by fewer and fewer dedicated people, with 22% of security professionals reporting recent layoffs at their company. The workforce reductions are an even more acute pain in cloud security, with 65% of cybersecurity and infosecurity professionals claiming burnout due to skill gaps. Even though a full 95% of IT decision makers feel their team has been negatively impacted by the cloud security skills gap, cloud native adoption continues, and analysts predict that, by 2025, 95% of new applications will be built using cloud native workloads.

Zero days like the XZ Backdoor are now a regular occurrence, making detection and response in cloud native environments more important than ever.

Also Read: Humanoid Robots And Their Potential Impact On the Future of Work

RAD Security has introduced multiple new features to help security teams adopt new innovation that will help them address these alarming trends and emerging threats:
– Amazon EKS Add-on: RAD Security is now available as an Amazon EKS Add-on in the AWS Marketplace for Containers. This means customers can now provision the real-time KSPM and runtime features of the RAD platform directly from EKS, for real-time visibility into their Kubernetes risk as well as signatureless cloud detection and response.
– Automated AI-Powered Investigation: RAD Security uses LLMs to quickly analyze multiple behavioral detections and determine whether an incident is malicious or benign, including real-time infrastructure and identity context.
– Findings Center: All incidents are now available in an easy to navigate console, making detection and investigation easier and quicker.
– RAD Open Source Catalog: New version details and new open source images have now been added to the RAD Catalog, detailing the changes in behavioral fingerprints over time and bolstering the behavioral workload fingerprint standard.

Schedule a meeting with the RAD Security team at the Black Hat Conference this week to discuss improving detection accuracy for attacks in your cloud environments. The team will be exhibiting at booth #219 in Startup City, and at 4:45PM EST they will be presenting at the Innovators and Investors Summit as one of the four finalists in the Startup Spotlight competition.

Don’t miss this out: More than 500 AI Models Run Optimized on Intel Core Ultra Processors

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]

The post RAD Security Launches First AI-Powered Incident Investigation with Behavioral Detection & Response Platform appeared first on AiThority.