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AI-Powered Smarter Media

AI-Powered Smarter Media

Transforming Retail Media: Personalization and Faster Monetization with Smarter Media Dentsu, a leading growth and transformation partner, has announced a strategic collaboration with Salesforce, the world’s #1 AI-powered CRM, to launch Smarter Media—an innovative solution designed to accelerate retail media monetization through personalized buying experiences powered by AI. Why Smarter Media Matters With shifting consumer priorities, personalized retail experiences are more critical than ever. Salesforce research highlights that: Smarter Media addresses this growing demand by enabling retailers to quickly adapt, offering tailored buying experiences that strengthen customer loyalty while driving revenue. What is Smarter Media? Smarter Media combines the power of Salesforce’s ecosystem—including Media Cloud, Sales Cloud, and Marketing Cloud Engagement—to deliver an end-to-end retail media solution. The platform assesses a brand’s retail media maturity, identifies gaps, and creates a roadmap to optimize media, technology, and skills. The solution simplifies access to advanced media technology, empowering brands to connect with customers 24/7, expand their customer base, and nurture long-term relationships. Key Features and Benefits 1. Comprehensive Assessment 2. AI-Powered Personalization 3. Built for Retail Media Success 4. Quick and Easy Adoption How Smarter Media Works Smarter Media combines Salesforce Sales Cloud’s leading sales and pipeline management tools with Media Cloud’s Advertising Sales Management application. The result is a solution that seamlessly supports both simple and complex retailer models: Real-World Value Across Retail By addressing challenges like fragmented media strategies and inaccessible technology, Smarter Media delivers transformative value for retailers: Driving Innovation Together Paul Lynch, Integrated Solutions Lead for Commerce and Retail at Dentsu UK&I, shared: “Smarter Media will democratize cutting-edge technology for brands by providing a one-stop solution to create personalized buying experiences. In today’s experience economy, maintaining compelling customer relationships has never been more vital.” Christopher Dean, SVP and GM for Communications, Media & Entertainment at Salesforce, added: “By combining Salesforce Media Cloud’s industry-specific solutions with Dentsu’s creative retail media expertise, we’re making advanced media technology accessible for retailers, helping them thrive in a competitive market.” The Future of Retail Media Smarter Media from Dentsu and Salesforce offers a transformative approach to retail media, empowering brands to deliver personalized experiences, improve customer loyalty, and accelerate revenue growth—all while leveraging cutting-edge AI and automation. With its ability to deliver value in just six months, Smarter Media is the ultimate solution for retailers looking to succeed in today’s fast-paced, customer-centric market. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Democratize Data with Einstein Copilot for Tableau

Democratize Data with Einstein Copilot for Tableau

Most workers today recognize the importance of rich data analytics in their jobs. However, 33% struggle to understand and generate insights from data. To address this, Salesforce has introduced Einstein Copilot for Tableau, which allows users of all skill levels to create complex data visualizations without extensive learning or coding. Democratize Data with Einstein Copilot for Tableau. Launched in April 2024, the beta version of this AI assistant features a user-friendly interface that simplifies the process with questions or simple commands. This facilitates the quick creation of comprehensive data presentations, including reports, dashboards, and various charts. Democratize Data with Einstein Copilot for Tableau Einstein Copilot for Tableau leverages a combination of AI technologies—natural language processing (NLP), machine learning (ML), and generative AI—to provide actionable insights. NLP enables conversational and intuitive interactions, while ML models process user queries and analyze data. Generative AI drives cognitive reasoning, planning, and creates insights, recommendations, and diagrams based on user inputs. By integrating with Tableau Cloud, Einstein Copilot accesses historical proprietary data, enables advanced data analysis, and translates user intent into actionable insights. It relies on Tableau’s analytics infrastructure to execute code and displays results through user-friendly visualizations and dashboards. Additionally, the Einstein Trust Layer secures and protects private data in Einstein Copilot. It authorizes inbound requests, ensuring users have necessary permissions to access specific data and safeguards model outputs to prevent the disclosure of confidential information. How Einstein Copilot for Tableau Transforms Requests into Insights To understand how Einstein Copilot for Tableau turns requests into actionable insights, let’s walk through each step of the interaction process: Einstein Copilot for Tableau democratizes access to data analytics, enabling all users to harness the power of data without needing extensive technical knowledge. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Nature Tech Alliance

Nature Tech Alliance

Exciting news! We are thrilled to introduce the Nature Tech Alliance, a groundbreaking initiative aimed at assisting companies in addressing pressing biodiversity challenges. Leading the charge are Planet, ERM, Salesforce, and NatureMetrics, joining forces to revolutionize how global corporations assess and manage their impact on nature. Alliance will focus on biodiversity measurement, management and disclosure, supporting businesses to get ahead of their nature impact reporting commitments. Formed during the World Economic Forum Annual Meeting in Davos, 2024, the Nature Tech Alliance is dedicated to expediting and expanding the evaluation, management, and disclosure of biodiversity impacts and dependencies on nature. Our goal is to drive a sustainable future for nature, people, and economies by providing companies with the tools and insights they need to understand and mitigate their impact on the environment. Through this alliance, companies will gain a comprehensive understanding of their business’s impact on nature and prepare to comply with new and forthcoming nature regulations and frameworks. This includes initiatives such as the Taskforce on Nature-related Financial Disclosures and the Corporate Sustainability Reporting Directive. At Planet, we are collaborating with other members of the alliance to provide industries with data-driven insights. Leveraging our satellite data and analytics alongside the expertise and tools of our partners, we are developing an integrated toolkit for biodiversity assessment. This toolkit will assist in value chain assessments, supplier engagement, and meeting reporting and compliance requirements. The powerful alliance will help businesses to overcome the common challenges faced in managing biodiversity integrity across industries. It will provide an integrated toolkit for biodiversity management and disclosure, including: Each member of the alliance brings unique knowledge and critical competencies to the table. ERM provides sustainability consulting and global delivery capabilities, Salesforce offers powerful technology solutions such as Net Zero Cloud, and NatureMetrics contributes its eDNA technology and on-the-ground biodiversity measurement expertise. Citizens of the planet are excited about the future of biodiversity and the opportunities for collaboration within this alliance. Thought leaders from each organization share their perspectives: Andrew Zolli, Chief Impact Officer at Planet: “We are at a pivotal moment in history where we have the technology and tools to quantify, monitor, and value our biodiversity. True collaboration is the next step, and we are thrilled to be part of this alliance to monitor and protect our world.” Matt Haddon, Global Leader for Biodiversity, Water & Nature at ERM: “By combining our capabilities, we can help organizations understand their nature-based risks and dependencies, enabling them to integrate nature into their business strategies and operations.” Tim Christophersen, VP, Climate Action at Salesforce: “To accelerate a successful transition to a net-zero and nature-positive future, businesses must measure, manage, and disclose their impact and reliance on nature. We are proud to form the Nature Tech Alliance and leverage our technologies to help other companies make a positive impact.” Dr. Kat Bruce, Founder of NatureMetrics: “This collaboration will provide full-spectrum biodiversity measurement, management, and disclosure for global corporations. Collaborations like this are critical for implementing solutions at scale and translating talk into real action on the ground.” About ERM As the world’s largest specialist sustainability consultancy, ERM partners with clients to operationalize sustainability at pace and scale, deploying a unique combination of strategic transformation and technical delivery capabilities. This approach helps clients to accelerate the integration of sustainability at every level of their business. With more than 50 years of experience, ERM’s diverse team of 8000+ experts in 40 countries and territories helps clients create innovative solutions to their sustainability challenges, unlocking commercial opportunities that meet the needs of today while preserving opportunity for future generations. Learn more here. About NatureMetrics NatureMetrics is a world leader in delivering nature data and intelligence. It uses cutting-edge technology to generate biodiversity data at scale using environmental DNA. NatureMetrics recently launched the world’s first Nature Intelligence Platform powered by eDNA, bringing a scalable solution to biodiversity monitoring, equipping businesses for the new nature reporting boom. NatureMetrics works with 500 plus clients in over 100 countries across a wide range of industries, including energy, extractives, food and drink, and financial services, helping them to get ahead of the emerging nature and biodiversity regulatory landscape. Visit: www.naturemetrics.com Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Customers Take On AI Hallucinations

Salesforce Customers Take On AI Hallucinations

Earlier this month, CRM specialists Salesforce hosted the latest edition of its World Tour Essentials event in Johannesburg. This event provided Salesforce with an opportunity to engage more personally with businesses in the region and showcase the AI-powered solutions it is developing, including the Einstein 1 platform. Now Salesforce Customers Take On AI Hallucinations. Einstein 1 is designed for AI-focused enterprises, leveraging existing CRM applications from Salesforce, along with data cloud and AI-powered tools. This platform aims to address key business challenges, one of which is the issue of generative AI hallucinations—where AI generates false information due to data gaps. A notable example of this issue was seen with Google’s Gemini, which produced bizarre and potentially harmful suggestions, like advising users to put epoxy glue on pizza. This occurred because the AI lacked sufficient data to generate accurate responses. While some companies continue to use the internet to train their platforms to avoid such hallucinations, businesses, particularly in the CRM field, cannot afford these inaccuracies. Salesforce has introduced a tool called Einstein 1 Studio to combat this problem. This tool allows business engineers and developers to create prompts and refine the overall experience of conversational platforms like Slack AI. During a media roundtable at the World Tour Essentials Johannesburg event, Linda Saunders, Salesforce’s Director of Solutions Engineering Africa, explained how Einstein 1 Studio helps mitigate AI hallucinations. “If you ask Einstein an ungrounded prompt like, ‘Please summarize the case for me,’ it may not know which case you’re referring to. By pulling metadata elements into the prompt and using certain word triggers, we can provide a much richer and more accurate AI response,” Saunders highlighted. She added that once a setup is built, it can be activated across multiple use cases, creating a consistent and efficient deployment process. Saunders also emphasized the importance of the trust layer within Einstein 1, which includes data grounding, audit trails, data masking, and mechanisms to prevent hallucinations. “The trust layer is integral to Einstein 1. Whether you build it or use the out-of-the-box capabilities, the trust layer ensures grounded data, audit trails, and other critical features,” Saunders explained. She also pointed out that Einstein 1’s building tools can address localization and tailor experiences to specific markets, like South Africa. “South African customers have unique needs compared to those in the US. This tool allows for prompt customization to better suit local business requirements,” Saunders noted. The configuration engine on top of Copilot functionality allows businesses to refine prompt engineering, ensuring that AI interactions are more tailored and effective. As AI integration becomes more widespread in business operations, addressing issues like AI hallucinations is crucial. According to Salesforce, Einstein 1 is designed with these considerations in mind, ensuring a reliable and accurate AI experience. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Can Tech Companies Use Generative AI for Good?

Can Tech Companies Use Generative AI for Good?

Responsible AI Innovation: Benefits and Strategies Can Tech Companies Use Generative AI for Good?. As generative AI reshapes our world, the conversation has largely focused on its risks and downsides. However, Suzanne DiBianca, EVP and Chief Impact Officer at Salesforce, highlights the often-overlooked benefits that AI can bring to society and the fight against climate change. Optimizing AI for Sustainability Salesforce is driven by a mission to reduce emissions, accelerate climate solutions, and advance inclusivity. According to DiBianca, with proper guardrails and ethical development, AI can significantly aid in achieving these goals. Key Strategies for Sustainable AI Development: Best Practices for Reducing Carbon Emissions in Software Development Technologists must follow best practices such as identifying and shutting down underused systems, moving storage to more energy-efficient options, and developing energy-efficient software code. Tracking Climate Impact Improving the tracking of climate impact involves simplifying reporting processes and investing in emissions-tracking solutions. DiBianca advises starting with a clear climate action plan, conducting energy usage audits, prioritizing renewable energy, and collaborating with suppliers to collect emissions data. Accelerating Climate Innovation Through AI Investments DiBianca emphasizes that reducing global emissions and limiting warming to 1.5°C requires urgent innovation and investment. Salesforce invests in companies using AI to address climate challenges, such as PanoAI, which deploys AI to detect and respond to wildfires. Driving Sustainability and Equity with AI To ensure AI benefits all, it is essential to integrate sustainability into the business core. Salesforce’s Sustainable AI Policy Principles guide the company’s efforts in minimizing environmental impact and promoting climate innovation. Upholding Responsibilities As a technology leader, Salesforce is committed to shaping AI’s impact on the world responsibly. DiBianca stresses the importance of a dual commitment to the planet and global communities, fostering a legacy of responsible AI innovation for future generations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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SMPL

SMPL

SMPL: A Virtual “Robot” for Embodied AI Embodied AI isn’t just for physical robots; it’s equally vital for virtual humans. Surprisingly, there’s a significant overlap between training robots to move and teaching avatars to behave like real people. Embodiment connects an AI agent‘s “brain” to a “body” that navigates and interacts with the world, whether real or virtual, grounding AI in a dynamic 3D environment. Skinned Multi Person Linear model is a realistic 3D model of the human body that is based on skinning and blend shapes and is learned from thousands of 3D body scans. Virtual Humans and SMPL The most common “body” for virtual humans is Skinned Multi Person Linear Model, a parametric 3D model encapsulating human shape and movement. SMPL represents body shape, pose, facial expressions, hand gestures, soft-tissue deformations, and more in about 100 numbers. This post explores why Skinned Multi Person Linear can be thought of as a “robot.” Virtual Humans as Robots The goal is to create virtual humans that behave like real ones, embodying AI that perceives, understands, plans, and executes actions to change its environment. In a recent talk at Stanford, I described virtual humans as “3D human foundation agents,” akin to robots. Replace the SMPL body with a humanoid robot and the virtual world with the real world, and the challenges are quite similar. Key Differences Between Virtual and Physical Robots However, virtual humans must move convincingly like real humans, which isn’t always necessary for physical robots. Another difference is physics; while real-world robots can’t ignore physics, virtual worlds can selectively model real-world physics, making training “SMPL robots” easier. Plus, SMPL never breaks down! SMPL as a Universal Humanoid SMPL serves as a “universal language” of behavior. At Meshcapade, we often call it a “secret decoder ring.” Various data forms like images, video, IMUs, 3D scans, or text can be encoded into SMPL format. This data can then be decoded back into the same formats or retargeted to new humanoid characters, such as game avatars using the Meshcapade UEFN plugin for Unreal or even physical robots. AMASS: A Warehouse of Human Behavior A first paper at Meshcapade was AMASS, the world’s largest collection of 3D human movement data in a unified format (SMPL-X). Modern AI requires large-scale data to learn human behavior, and most deep learning methods modeling human motion rely on AMASS for training data. Researchers mine AMASS to train diffusion models to generate human movement. Adding text labels (see BABEL) enables conditioning generative models of motion on text. With speech and gesture data (see EMAGE), full-body avatars can be driven purely by speech. AMASS continues to grow, aiming to catalog all human behaviors. Learning from Humans At Perceiving Systems and Meshcapade, we use data like AMASS to train virtual humans and robots. For example, OmiH2O uses AMASS to retarget SMPL to a humanoid robot, and reinforcement learning methods mimic human behavior using AMASS data. Methods like WHAM can estimate SMPL from video in 3D world coordinates, crucial for robotic applications. This allows robots to learn from video demonstrations encoded into SMPL format, using an encoder for input and a decoder for output retargeting. SMPL as the “Latent Space” In machine learning, encoder-decoder architectures encode data into a latent space, which is typically compact. SMPL, though not truly latent because its parameters are interpretable, serves as a compact representation of humans. It factors body shape from pose, modeling correlations with “pose corrective” blend shapes and using principal component analysis for data compression. Summary Embodiment is crucial for both physical robots and virtual humans. Viewing virtual humans as robots can benefit robotics. We consider SMPL a virtual robot, collecting human behavior data at scale, learning from it, and retargeting this behavior to other virtual or physical embodiments. SMPL acts as a “universal language” for human movement, translating data into and out of various forms of embodiment. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Cautionary AI Tale

A Cautionary AI Tale

Oliver Lovstrom, an AI student, wrote an interesting perspective on artificial intelligence, a cautionary AI tale, if you will. The Theory and Fairy Tale My first introduction to artificial intelligence was during high school when I began exploring its theories and captivating aspects. In 2018, as self-driving cars were gaining traction, I decided to create a simple autonomous vehicle for my final project. This project filled me with excitement and hope, spurring my continued interest and learning in AI. However, I had no idea that within a few years, AI would become significantly more advanced and accessible, reaching the masses through affordable robots. For instance, who could have imagined that just two years later, we would have access to incredible AI models like ChatGPT and Gemini, developed by tech giants? The Dark Side of Accessibility My concerns grew as I observed the surge in global cybersecurity issues driven by advanced language model-powered bots. Nowadays, it’s rare to go a day without hearing about some form of cybercrime somewhere in the world. A Brief Intro to AI for Beginners To understand the risks associated with AI, we must first comprehend what AI is and its inspiration: the human brain. In biology, I learned that the human brain consists of neurons, which have two main functions: Neurons communicate with sensory organs or other neurons, determining the signals they send through learning. Throughout our lives, we learn to associate different external stimuli (inputs) with sensory outputs, like emotions. Imagine returning to your childhood home. Walking in, you are immediately overwhelmed by nostalgia. This is a learned response, where the sensory input (the scene) passes through a network of billions of neurons, triggering an emotional output. Similarly, I began learning about artificial neural networks, which mimic this behavior in computers. Artificial Neural Networks Just as biological neurons communicate within our brains, artificial neural networks try to replicate this in computers. Each dot in the graph above represents an artificial neuron, all connected and communicating with one another. Sensory inputs, like a scene, enter the network, and the resulting output, such as an emotion, emerges from the network’s processing. A unique feature of these networks is their ability to learn. Initially, an untrained neural network might produce random outputs for a given input. However, with training, these networks learn to associate specific inputs with particular outputs, mirroring the learning process of the human brain. This capability can be leveraged to handle tedious tasks, but there are deeper implications to explore. The Wishing Well As AI technology advances, it begins to resemble a wishing well from a fairy tale—a tool that could fulfill any desire, for better or worse. In 2022, the release of ChatGPT and various generative AI tools astonished many. For the first time, people had free access to a system capable of generating coherent and contextually appropriate responses to almost any prompt. And this is just the beginning. Multimodal AI and the Next Step I explored multimodal AI, which allows the processing of data in different formats, such as text, images, audio, and possibly even physical actions. This development supports the “wishing well” hypothesis, but also revealed a darker side of AI. The Villains While a wishing well in fairy tales is associated with good intentions and moral outcomes, the reality of AI is more complex. The morality of AI usage depends on the people who wield it, and the potential for harm by a single bad actor is immense. The Big Actors and Bad Apples The control of AI technology is likely to be held by powerful entities, whether governments or private corporations. Speculating on their use of this technology can be unsettling. While we might hope AI acts as a deterrent, similar to nuclear weapons, AI’s invisibility and potential for silent harm make it particularly dangerous. We are already witnessing malicious uses of AI, from fake kidnappings to deepfakes, impacting everyone from ordinary people to politicians. As AI becomes more accessible, the risk of bad actors exploiting it grows. Even if AI maintains peace on a global scale, the issue of individuals causing harm remains—a few bad apples can spoil the bunch. Unexpected Actions and the Future AI systems today can perform unexpected actions, often through jailbreaking—manipulating models to give unintended information. While currently, the consequences might seem minor, they could escalate significantly in the future. AI does not follow predetermined rules but chooses the “best” path to achieve a goal, often learned independently from human oversight. This unpredictability, especially in multimodal models, is alarming. Consider an AI tasked with making pancakes. It might need money for ingredients and, determined by its learning, might resort to creating deepfakes for blackmail. This scenario, though seemingly absurd, highlights potential dangers as AI evolves with the growth of IoT, quantum computing, and big data, leading to superintelligent, self-managing systems. As AI surpasses human intelligence, more issues will emerge, potentially leading to a loss of control. Dr. Yildiz, an AI expert, highlighted these concerns in a story titled “Artificial Intelligence Does Not Concern Me, but Artificial Super-Intelligence Frightens Me.” Hope and Optimism Despite the fears surrounding AI, I remain hopeful. We are still in the early stages of this technology, providing ample time to course-correct. This can be achieved through recognizing the risks, fostering ethical AI systems, and raising a morally conscious new generation. Although I emphasized potential dangers, my intent is not to incite fear. Like previous industrial and digital revolutions, AI has the potential to greatly enhance our lives. I stay optimistic and continue my studies to contribute positively to the field. The takeaway from my story is that by using AI ethically and collaboratively, we can harness its power for positive change and a better future for everyone. This article by Oliver Lovstrom originally was published by Medium, here. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a

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AI for Marketing and Retail

AI for Marketing and Retail

Salesforce Expands AI Capabilities for Marketing and Retail with Einstein Copilot Salesforce is making waves in the marketing and retail sectors by enhancing its Einstein Copilot feature, bringing advanced AI tools even closer to its users. AI for Marketing and Retail. For those unfamiliar with Salesforce, it offers Einstein 1, a comprehensive platform integrating AI and machine learning across its various applications. Einstein Copilot, a part of this platform, functions as an AI-powered assistant designed to provide real-time assistance, automate tasks, and deliver contextual insights to boost productivity. New Additions: Einstein Copilot for Marketers and Merchants Salesforce has recently announced two exciting additions: Einstein Copilot for Marketers and Einstein Copilot for Merchants. Einstein Copilot for Marketers: Einstein Copilot for Merchants: Availability Einstein Copilot for Marketers is set to be generally available this summer, while Einstein Copilot for Merchants will enter the beta stage in the autumn. Leadership Insight “With the Einstein 1 Platform, we’re giving organizations the power to unify all of their data on one trusted platform,” said Ariel Kelman, President and CMO of Salesforce. “This is the key to getting results from generative AI that are actually useful in driving your business forward.” About Salesforce Founded in 1999, Salesforce is a cloud-based software company renowned as one of the best CRM software providers. With over 72,000 employees globally and an annual revenue of .49 billion, Salesforce continues to lead in innovation and customer satisfaction. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Improve Patient Care and Trust

Improve Patient Care and Trust

A recent survey conducted by Kyruus Health and shared with HealthPayerIntelligence reveals that consumers are demanding more accurate online provider data from payers to enhance access to care. Healthcare solutions from Tectonic and Salesforce improve patient care and trust by improving data accuracy. The survey, fielded by Wakefield Research in April 2024, involved 1,000 healthcare consumers. Nearly three-quarters of respondents (72%) had private health insurance, with Medicare being the second most common form of coverage (18%). The participants represented an even distribution across U.S. regions and age groups, with 57% identifying as women. Payers have historically struggled to maintain up-to-date provider directories, and this survey highlights the significant impact of these challenges. About 30% of consumers reported skipping care due to inaccurate provider information, with 70% of them seeking this data online. Consumers primarily rely on health plan websites or apps for provider information, with 32% naming these platforms as their first resource. Medicaid enrollees were particularly dependent on their plan’s digital resources, with 64% turning to these tools first. Besides health plan websites and apps, consumers also used general internet searches, provider or clinic websites, and healthcare information sites like WebMD. Social media platforms were also popular for care searches, with 77% of users turning to Facebook and 61% to YouTube. The survey also revealed that payers often fail to provide accurate cost predictions. Only 32% of respondents said their health plans offered accurate cost information. Price transparency tools are particularly important to younger generations, with 76% of Millennials and 80% of Gen Z respondents using these tools. However, 40% of Baby Boomers were unsure if their plans even offered such tools. Among those who did use them, 34% found that the tools presented incorrect provider data, with 45% of Gen Z reporting this issue. Inaccurate provider information can lead to significant negative consequences for consumers, including delays in accessing care, difficulties contacting preferred providers, and higher costs. Some consumers even reported accidentally receiving out-of-network care or forgoing care altogether due to these inaccuracies. These experiences not only hinder access to care but also damage consumer trust in their healthcare providers and payers. Overall, 80% of respondents said that inaccurate provider data affected their trust, with 27% losing trust in their health plans and 22% losing trust in their providers. The survey results underscore a clear call to action. Over 60% of consumers, and nearly 75% of Gen Z specifically, want their health plans to provide more accurate data. Tectonic has decades of experience applying Salesforce solutions to health care providers and payers. To address these concerns, the report recommends that health plans take three key steps: First, engage with members through appropriate channels, including social media. Second, unify and validate their provider data to ensure accuracy. Third, introduce self-service capabilities within their digital platforms to empower consumers. Reach out to Tectonic today if your organization needs help applying these three steps. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Gen AI Unleased With Vector Database

Gen AI Unleased With Vector Database

Salesforce Unveils Data Cloud Vector Database with GenAI Integration Salesforce has officially launched its Data Cloud Vector Database, leveraging GenAI to rapidly process a company’s vast collection of PDFs, emails, transcripts, online reviews, and other unstructured data. Gen AI Unleased With Vector Database. Rahul Auradkar, Executive Vice President and General Manager of Salesforce Unified Data Services and Einstein Units, highlighted the efficiency gains in a one-on-one briefing with InformationWeek. Auradkar demonstrated the new capabilities through a live demo, showcasing the potential of the Data Cloud Vector Database. Enhanced Efficiency and Data Utilization The new Data Cloud integrates with the Einstein 1 platform, combining unstructured and structured data for rapid analysis by sales, marketing, and customer service teams. This integration significantly enhances the accuracy of Einstein Copilot, Salesforce’s enterprise conversational AI assistant. Gen AI Unleased With Vector Database Auradkar demonstrated how a customer service query could retrieve multiple relevant results within seconds. This process, which typically takes hours of manual effort, now leverages unstructured data, which makes up 90% of customer data, to deliver swift and accurate results. “This advancement allows our customers to harness the full potential of 90% of their enterprise data—unstructured data that has been underutilized or siloed—to drive use cases, AI, automation, and analytics experiences across both structured and unstructured data,” Auradkar explained. Comprehensive Data Management Using Salesforce’s Einstein 1 platform, Data Cloud enables users to ingest, store, unify, index, and perform semantic queries on unstructured data across all applications. This data encompasses diverse unstructured content from websites, social media platforms, and other sources, resulting in more accurate outcomes and insights. Auradkar emphasized, “This represents an order of magnitude improvement in productivity and customer satisfaction. For instance, a large shipping company with thousands of customer cases can now categorize and access necessary information far more efficiently.” Additional Announcements Salesforce also introduced several new AI and Data Cloud features: Auradkar noted that these innovations enhance Salesforce’s competitive edge by prioritizing flexibility and enabling customers to take control of their data. “We’ll continue on this journey,” Auradkar said. “Our future investments will focus on how this product evolves and scales. We’re building significant flexibility for our customers to use any model they choose, including any large language model.” For more insights and updates, visit Salesforce’s official announcements and stay tuned for further developments. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Dynamic Content Powered Email

Dynamic Content Powered Email

Elevating Email Marketing with Dynamic Content Customers don’t want to feel like just another number to your brand. Relying on a generic “batch and blast” email marketing strategy is likely to land you in the customer’s spam filters—or worse, prompt them to unsubscribe. However, with Dynamic Content Powered Email, you can create a relevant and timely experience they’ll remember for all the right reasons. The Power of Personalization In an era where privacy and security dominate the headlines, it’s surprising that 83% of consumers are willing to share personal data for more personalized experiences. This isn’t just an interesting tidbit—it’s proof that people expect and value personalized experiences from brands. This tradeoff—data for personalization—presents a significant opportunity for marketers who can uphold their end of the bargain. Nowhere is this more evident than in the inbox. Dynamic email content allows for the creation of personalized messages that update when the email is opened, meeting readers’ expectations for tailored communication. The Importance of Dynamic Email Content Modern email marketing must prioritize engaging and relevant content to avoid poor performance and potential relegation to spam folders. Recent developments, such as the loss of third-party cookies, make it increasingly challenging to acquire the right data for personalization. Let’s explore some tactics and resources to achieve quick email marketing wins without the heavy lifting, by automating impactful experiences in the inbox. Understanding Dynamic Email Content Dynamic email content, often called live email content, refers to messages that change based on the subscriber’s personal preferences or history with your website. Unlike static ads, dynamic content offers a tailored shopping experience, increasing engagement and fostering brand loyalty. For example, using dynamic elements such as live polls or customized product recommendations can make subscribers feel valued and understood. Interactive emails enhance the overall experience and encourage deeper engagement. Case Studies in Dynamic Email Success Dynamic content engages audiences and prompts action, crucial for both business success and email program health. Email engagement metrics influence whether your emails are delivered to the inbox or spam folder, making engaging content essential for ISP trust. Not just customer trust. Leveraging First- and Zero-Party Data First-party data is now more important than ever. Email provides a direct line to subscribers, enabling the collection of valuable insights into their preferences and behaviors. This data can fuel further personalization efforts. For example, UK hospitality brand icelolly.com used dynamic email content to display searched and abandoned deals, resulting in a 35% higher open rate, a 201% increase in click-through rate, and a 45% increase in conversion rate. Popular Types of Dynamic Email Content Implementing Dynamic Email Content Simply Personalization with dynamic email content doesn’t have to be resource-intensive. No-code solutions or templates can streamline the process, allowing ongoing implementation with minimal effort. For instance, PrettyLittleThing used automation in birthday emails to show the correct star sign content based on the opening date, driving a 38% increase in click-through rates. Dynamic Content Powered Email has emerged as a powerful tool for marketers aiming to meet and exceed consumer expectations. By incorporating dynamic elements—such as live polls, countdown timers, and personalized images—marketers can create engaging, memorable experiences that build stronger customer relationships and drive brand loyalty. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Data Cloud Vector Database and Hyperforce

Data Cloud Vector Database and Hyperforce

Salesforce World Tour Highlights: Data Cloud Vector Database and Hyperforce At the Salesforce World Tour on June 6, 2024, at the Excel Centre in east London, the focus was on advancements in the Data Cloud and Slack platforms. The event, sponsored by AWS, Cognizant, Deloitte, and PWC, showcased significant innovations, particularly for GenAI enthusiasts. Data Cloud Vector Database and Hyperforce. Vector Database in Data Cloud A key highlight was the announcement of the general availability of a Vector Database capability within the Data Cloud, integrated into the Einstein 1 Platform. This capability enhances Salesforce’s CRM platform, Customer 360, by combining structured and unstructured data about end-users. The Vector Database collects, ingests, and unifies data, allowing enterprises to deploy GenAI across all applications without needing to fine-tune an off-the-shelf large language model (LLM). Addressing Data Fragmentation Salesforce reports that approximately 80% of customer data is dispersed across various corporate departments in an unstructured format, trapped in PDFs, emails, chat conversations, and transcripts. The Vector Database unifies this fragmented data, creating a comprehensive profile of the customer journey. This unified approach not only improves customer engagement but also enhances organizational agility. By consolidating data from all corporate silos, companies can quickly and efficiently address issues such as product recalls and returns. Hyperforce: Enhancing Data Residency and Compliance During the keynote, Salesforce emphasized the importance of personalization in customer engagement and the benefits of deploying GenAI in customer-facing sectors. The event highlighted the need to overcome the fear and mistrust of GenAI and showcased how enterprises can enhance employee productivity through upskilling in GenAI technologies. One notable announcement was the general availability of Hyperforce, a solution designed to address data residency issues by integrating all Salesforce applications under the same compliance, security, privacy, and scalability standards. Built for the public cloud and composed of code rather than hardware, Hyperforce ensures safe delivery of applications worldwide, offering a common layer for deploying all application stacks and handling data compliance in a fragmented technology landscape. Salesforce AI Center The Salesforce AI Center was also introduced at the event. The first of its kind, located in the Blue Fin Building near Blackfriars, London, this center will support AI experts, Salesforce partners, and customers, facilitating training and upskilling programs. Set to open on June 18, 2024, the center aims to upskill 100,000 developers worldwide and is part of Salesforce’s $4 billion investment in the UK and Ireland. Industry Reactions and Future Prospects GlobalData senior analyst Beatriz Valle commented on Salesforce’s continued integration of GenAI across its portfolio, including platforms like Tableau, Einstein for analytics, and Slack for collaboration. According to Salesforce, the Data Cloud tool leverages all metadata in the Einstein 1 Platform, connecting unstructured and structured data, reducing the need for fine-tuning LLMs, and enhancing the accuracy of results delivered by Einstein Copilot, Salesforce’s conversational AI assistant. Vector databases, while not new, have gained prominence due to the GenAI revolution. They power the retrieval-augmented generation (RAG) technique, linking proprietary data with large language models like OpenAI’s GPT-4, enabling enterprises to generate more accurate results. Competitors such as Oracle, Amazon, Microsoft, and Google also offer vector databases, but Salesforce’s early investments in GenAI are proving fruitful with the launch of the Data Cloud Vector Database. Data Cloud Vector Database and Hyperforce Salesforce’s AI-powered integration solutions, highlighted during the World Tour, underscore the company’s commitment to advancing digital transformation. By leveraging GenAI and innovative tools like the Vector Database and Hyperforce, Salesforce is enabling enterprises to overcome the challenges of data fragmentation and compliance, paving the way for a more agile and competitive digital future. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Legacy Chat Service Retirement

Salesforce Summer 24 Customization Release

Customization Salesforce Summer 24 Customization Release Manage users more easily with the user access, public group, permission set, and permission set group summaries. Give record page users more of what they need where and when they need it with Lightning record page enhancements such as blank space support and visibility rules on individual tabs. Salesforce Summer 24 Customization Release Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Consumer Chatbot Technology

Consumer Chatbot Technology

The Reality Behind AI Chatbots and the Path to Autonomous AI In the rush to adopt the latest Consumer Chatbot Technology, it’s easy to overlook a fundamental reality: consumer chatbot technology isn’t ready for enterprise use—and it likely never will be. The reason is simple: AI assistants are only as effective as the data that powers them. Most large language models (LLMs) are trained on data from public websites, which lack the specific business and customer data that enterprises need. This means consumer bots can’t adequately assist employees in selling products, marketing merchandise, or improving productivity, as they lack the necessary personalization and business context. To achieve the vision of AI that goes beyond simple chatbots performing basic tasks—like drafting emails, essays, blogs, or graphics—to a more advanced role where AI acts autonomously and addresses business-critical needs, a different approach is needed. This vision involves AI taking action with minimal human intervention, using digital agents to identify and respond to these needs. At Salesforce, we are pursuing a clear path to AI that not only takes action but also automates routine tasks, all while adhering to established business rules, permissions, and context. Instead of relying solely on LLMs, which primarily focus on generating human-like text, future AI assistants will depend on large action models (LAMs) that integrate decision-making and action-taking capabilities. The Journey Toward AI Autonomy Our journey towards this vision began with the Salesforce Data Cloud, a robust data engine built on the Einstein 1 Platform. This platform integrates data from across the enterprise and third-party repositories, enabling companies to activate their data, automate workflows, personalize customer interactions, and develop smarter AI solutions. Recognizing the shift from generative AI to autonomous AI, Salesforce introduced Einstein Copilot, the industry’s first conversational, enterprise-class AI assistant. Integrated across the Salesforce ecosystem, Einstein Copilot utilizes an organization’s data, whether it’s behind a firewall or in an external data lake, to act as a reasoning engine. It interprets user intents, interacts with the most suitable AI model, solves problems, generates relevant content, and provides decision-making support. Expanding the Role of AI in Business Since its launch in February 2024, Salesforce has been expanding Einstein Copilot’s library of actions to meet specific business needs in sales, service, marketing, data analysis, and industries like ecommerce, financial services, healthcare, and education. These “actions” are akin to LEGO blocks—discrete tasks that can be assembled to achieve desired project outcomes. For example, a sales representative might use Einstein Copilot to generate a personalized close plan, gain insights into why a deal may not close, or review whether pricing was discussed in a recent call. Einstein Copilot then orchestrates these tasks, provides recommendations, and compiles everything into a detailed report. The ultimate goal is for AI not only to gather and organize information but also to take proactive action. Imagine a sales representative instructing their digital agent to set up meetings with top prospects in a specific territory. The AI could not only identify suitable contacts but also suggest meeting times, plan travel schedules, draft emails, and even create talking points—all of which it could execute autonomously with the representative’s approval. Tectonic dreams of the day AI is smart enough to interpret our search engine typos and produce the results for what we were actually looking for! The Future of AI Autonomy The possibilities for semi-autonomous or fully autonomous AI are vast. As we continue to develop and refine these technologies, the potential for AI to transform business processes and decision-making becomes increasingly tangible. At Salesforce, they are committed to leading this charge, ensuring that our AI solutions not only meet but exceed the expectations of enterprises worldwide. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. It will not happen overnight. The technology needs to advance, organizations and people have to be able to trust AI and be trained to use it in the right ways, and more work will need to be done to ensure the right balance between human involvement and AI autonomy. But with our continued investment in CRM, data, and trusted AI, we will achieve that vision before too long. Salesforce is in a strong position to deliver on all of them because of the volume and breadth of data housed in Data Cloud, the heavy workflow traffic in our Customer 360 CRM, and the fact we’ve delivered an enterprise-class copilot that is rapidly expanding its library of actions. Jayesh Govindarajan, Senior Vice President, Salesforce AI Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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