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Hollywood's Fear of AI

Hollywood’s Fear of AI

For the past 18 months, there has been a focus on why Generative AI (GenAI) poses a disruptive threat to Hollywood. Hollywood’s Fear of AI is entirely reasonable. This insight, most recently detailed in an investor presentation, highlights how GenAI will democratize high production-value video creation and exacerbate the low-end disruption of Hollywood already underway by creator content. The exploration now turns to another angle: why it will be challenging for major studios to capitalize on these tools, particularly AI video generators like Sora, Veo, and Runway Gen-3. Hollywood’s Fear of AI. Key Points: Early Adoption Outside Major Studios: The most promising early use cases for AI video generators will be outside major Hollywood studios. These include empowering independent creators and producers, as well as applications in advertising, music videos, and educational or corporate videos. AI won’t replace Hollywood but poses a bigger risk of disrupting it, requiring a disruptive innovation and incumbents who can’t respond effectively. Detailed Analysis: Sora’s Impact: AI has been part of the TV and film production process for a long time. Many studios use AI for concept art, localization services, and post-production work. However, AI video generators like Sora represent a new way to create video, potentially replacing much of the principal photography. The announcement of Sora was a watershed moment, showcasing radical improvements in temporal coherence, character consistency, and video length. Hollywood’s Fear of AI Legal Quagmire: Hollywood’s extensive legal framework complicates the adoption of GenAI. Studios need clear legal resolutions before extensively using GenAI in principal photography. The primary concerns are: Technical Limitations: AI video generators still fall short of professional standards. Issues include limited training sets, lack of understanding of physics, history, and geography, and insufficient control over video production elements like camera angles, lighting, and film stock. Near-Term Use Cases: Conclusion: While AI video generators won’t replace traditional Hollywood production soon, they have the potential to significantly disrupt the industry. The early adoption of these tools will likely occur outside the major studios, empowering independent creators and other sectors like advertising and education. The evolution of AI video generators continues to pose both challenges and opportunities for Hollywood. 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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Salesforce Native Explained

Salesforce Native Explained

What Does Salesforce-Native Mean? SFDC-native refers to products that are built entirely within the Salesforce platform. These products do not require integration through the Salesforce API, as they are inherently part of Salesforce and designed specifically for its environment. Aren’t Most Salesforce Products Built Native? No, most products that claim to be SFDC-native are not fully native. Many are partially built within Salesforce or use Salesforce reports, but they still operate or were developed outside the Salesforce platform. This can be misleading since a product is only truly native if it is entirely built and operates within Salesforce. How Can I Tell if a Product is 100% Native? To determine if a product is 100% native, you can start by checking the Salesforce AppExchange. Additionally, you should ask your provider these questions: If the product is hosted or its data is stored on an external server and not within Salesforce, then it is not a native product. Why Should I Consider a 100% Native Product? Enhanced Security Since a native product doesn’t need to integrate with Salesforce, there’s no need to export data to external servers, which can be vulnerable. Everything remains within Salesforce, adhering to its already robust security settings. Accuracy and Speed A 100% native product ensures real-time data accuracy, eliminating concerns about syncing issues. You can always trust that the data you’re working with is current. Trust Products built within Salesforce follow Salesforce’s best practices and security policies. This ensures that you can trust these products as much as you trust Salesforce. Additionally, since they run on the same server as Salesforce, your product’s uptime is aligned with Salesforce’s uptime. Simplified Tech Stack and Alignment A native solution is easier to manage because it doesn’t require additional user log-ins or new skills to learn. When users log into Salesforce, they automatically access the native product’s features, reducing training needs and improving adoption rates. This also promotes better team alignment by providing a single source of truth, enhancing communication. SFDC-native means that a product is built entirely within Salesforce, using its core technologies and development environment. Native products are written for the platform and don’t need to be integrated using the Salesforce API. When an app is native to Salesforce, that means that an app is dedicated and committed to Salesforce. Non-native apps are more versatile in that they can typically integrate with a variety of different CRMs, but when you use a native Salesforce app, you work with a Salesforce expert. What does platform native mean? Native applications and platforms However, in the context of mobile web apps, the term native app means any application written to work on a specific device platform. The two main mobile OS platforms are Apple’s iOS and Google’s Android. Developers write native apps in the code used for the device and its OS. Non-SFDC Applications means a Web-based, mobile, offline or other software application functionality that is provided by You or a third party and interoperates with a Service, including, for example, an application that is developed by or for You, is listed on a Marketplace, is identified as Salesforce Labs or by a similar designation, or is an open source software product including e.g. the technologies commonly referred to as Non Profit Starter Pack (“NPSP”) and Higher Education Data Architecture (“HEDA”) and that are subject to the terms stated during the installation process and/or located on the landing page during their use. 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 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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Salesforce Essentials and Salesforce Professional

Salesforce Essentials and Salesforce Professional

Salesforce offers two primary CRM solutions: Salesforce Essentials and Salesforce Professional, each tailored to different business needs. Salesforce Essentials: Salesforce Essentials is designed for small businesses, offering fundamental CRM tools at an affordable price. It’s ideal for teams of up to five members and provides a unified view of customer interactions across multiple channels, including email, chat, social media, and phone. This platform simplifies customer support with a consolidated help center for common inquiries. Priced at $25 per month, Essentials is budget-friendly and easy to set up, making it suitable for startups and small teams looking for a straightforward CRM solution. Salesforce Professional: On the other hand, Salesforce Professional targets larger businesses with more complex CRM requirements. It extends beyond basic CRM functionalities to include advanced features such as lead management, customizable sales processes, and comprehensive reporting capabilities. Key attributes of Professional include forecasting tools, Einstein Activity Capture for enhanced productivity insights, and a mobile app with full offline functionality. Priced at per user per month, Professional caters to businesses needing extensive customization options and deep data analysis capabilities to manage complex sales processes and customer relationships effectively. Comparison: Salesforce Essentials Salesforce Professional Price $25 per month $80 per user, per month User limit Up to 5 users Unlimited users Reporting and Dashboards Basic reporting capabilities Customizable reports and dashboards Mobile App Functionality Limited Full offline functionality Email Integration Basic email integration Advanced integration with Outlook and Gmail Customization Limited customization options Extensive customization options Customization The customization options in Essentials are limited, which is often sufficient for smaller businesses that don’t need complex customization. Extensive customization options in Professional allow larger businesses to tailor the CRM to their specific processes and needs, a critical feature for complex business structures. Salesforce Essentials is widely considered a beneficial instrument for small enterprises, providing essential features for customer relationship management, sales, and marketing automation. It is valued for its accessibility, user-friendly interface, and all-in-one platform. Strong choices for customer service are provided, and it connects effectively with other corporate tools and is expandable. The software has a learning curve for certain users, and you can’t access advanced functions unless you pay more. A reliable internet connection is necessary for the often intricate setting and customization. Concerns are also raised about reporting functionality and extra costs for premium services that exceed the basic subscription charge. Users of Salesforce Professional recognize the platform’s extensive features and ease of use. They also commend it for its ability to integrate with other platforms, like WhatsApp. Some people do, however, feel that the UI could be more contemporary and intuitive. There is disagreement over the frequency of updates and the unresponsiveness of various parts of the customer support. Users value the tool’s capacity to enhance workday routines, its intuitive design, and its simplicity in integrating with lead generation and sales channels. The cost is observed to be greater than that of comparable suppliers, and third parties are frequently needed for the implementation phase. Can Salesforce Essentials scale with my growing business? Salesforce Essentials is tailored for small businesses and startups and while it offers essential CRM tools, it has limitations in scalability due to its user cap and basic feature set. For businesses anticipating significant growth, transitioning to Salesforce Professional or another higher-tier Salesforce product might be necessary. Conclusion: Choosing between Salesforce Essentials and Salesforce Professional depends on the size of your business, your budget, and the complexity of your CRM needs. Essentials is suitable for small teams and startups looking for an affordable, easy-to-use CRM solution. In contrast, Professional is geared towards larger businesses that require advanced features, customization options, and robust reporting capabilities to manage complex sales operations effectively. 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 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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Automated LinkedIn Prospecting

Automated LinkedIn Prospecting

Salesflow, an award-winning LinkedIn outreach automation platform, announces native integrations with a range of popular CRM systems. London, United Kingdom – June 14, 2024 —Automated LinkedIn Prospecting The automated LinkedIn lead generation tool now offers seamless integration with HubSpot, Zapier, Salesforce, and PipeDrive, with further additions expected in the coming months. The firm states that it now takes less than five minutes for clients to begin using LinkedIn automation through their existing CRM platform, allowing them to continue using familiar tools and workflows. More details can be found at https://salesflow.io/automation-software-improve-pipeline/ Salesflow explains that the new CRM integrations have applications for sales teams, small companies, and LinkedIn-as-as-Service agencies. The firm’s award-winning software is designed to automate multiple stages in the LinkedIn lead generation process, allowing teams to focus their energies on the most attractive prospects. According to LinkedIn’s own statistics, over 80% of B2B marketers say that they achieve the greatest results when social selling through the platform, when compared to other social media networks. However, creating an outreach campaign that retains a personal element can be a time-consuming task, which can limit its usefulness for smaller organizations. Salesflow is designed to create highly automated LinkedIn campaigns, while still offering the ability to include unique keywords that make messages more personal. With the new CRM integrations, the firm has progressed the automation several steps further, with the goal of making the process as fast and efficient as possible. “Salesflow is a cloud-based automation tool using static IPs to ensure a secure prospecting outreach while running on autopilot,” a company representative explained. “You can also now set up integrations to get data from LinkedIn sent directly into your CRM system, and you can begin to see new leads filtering through almost immediately.” About Salesflow Peer-to-peer software review site G2 identified Salesflow as a “High Performer” in the lead generation automation category for the spring and summer of this year, and recently upgraded that rating to “Leader” for both the European and US markets. The system is now used by several major organizations, including HubSpot, Verizon, and Visyond. “Salesflow is awesome and is a must-have for B2B social selling,” one company director recently stated. “This brilliant platform saves us a huge amount of time and money on lead generation, it reduces stress, and gets us connected to relevant prospects across our target industries. Best of all, it does all of that really fast.” Interested parties can find more information by visiting https://salesflow.io/automation-software-improve-pipeline/ 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 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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Unity Catalog Open Sourced by Databricks

Unity Catalog Open Sourced by Databricks

Databricks Announces Open Sourcing of Unity Catalog for Data and AI Governance Databricks, the Data and AI company, has announced the open-sourcing of Unity Catalog, the industry’s only unified solution for data and artificial intelligence (AI) governance across clouds, data formats, and data platforms. This initiative underscores Databricks’ commitment to open ecosystems, providing customers with the flexibility and control they need without vendor lock-in. The announcement marks a new era for open catalog standards for data and AI, with support from major partners such as Amazon Web Services (AWS), Google Cloud, Microsoft, NVIDIA, Salesforce, and others. Unity Catalog Open Sourced by Databricks. Key Features of Unity Catalog OSS Interoperability: Unity Catalog OSS offers a universal interface supporting any data format and compute engine. It can read tables with Delta Lake, Apache Iceberg™, and Apache Hudi™ clients via Delta Lake UniForm, and supports the Iceberg REST Catalog and Hive Metastore (HMS) interface standards. It is interoperable with all major cloud platforms, compute engines, and data and AI platforms. Unified Governance: Unity Catalog OSS enables unified governance across tabular data, non-tabular data, and AI assets such as ML models and generative AI tools, simplifying management, discovery, and development at scale. Openness: With open APIs and an Apache 2.0 licensed open source server, Unity Catalog OSS maximizes flexibility and customer choice by enabling broad interoperability across various engines, tools, and platforms. Industry and Partner Support Unity Catalog OSS is the industry’s only universal catalog for data and AI. Since its introduction in 2021, Unity Catalog has helped over 10,000 organizations break down silos created by multiple single-purpose solutions. Customer Testimonials: Supporting Cloud Partners: Supporting Data and AI Partners: The Future of Data and AI Governance With the open-sourcing of Unity Catalog, Databricks continues to lead in data and AI governance, fostering an ecosystem of interoperable tools, universal support for data and AI assets, and built-in security. Unity Catalog OSS will be available at the Data + AI Summit, furthering Databricks’ mission to empower organizations with the tools needed for modern data and AI applications. 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 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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Salesforce Spiff

Salesforce Spiff

Incentive Compensation Management Boost seller motivation and performance with incentive compensation management software that offers real-time commission visibility. Salesforce Spiff. Automate commission calculations, reduce administrative tasks, and improve departmental alignment with compensation plans geared for revenue growth. Automate Commissions and Motivate Sellers Enhance collaboration across departments and align go-to-market priorities with effective incentive compensation management. Customized Rep Statements Empower sellers by providing commission statements, tracking progress against goals, and estimating potential earnings. Use commission tracing functionality to eliminate confusion and align organizational priorities with seller motivations. In-App Comments and Notifications Manage questions, comments, and disputes efficiently within a single platform. Promote cross-organizational collaboration through real-time comments and notifications. Commission Estimator Allow sellers to predict future earnings by providing data-driven insights into incentive estimates early in the sales process. This helps sellers and managers focus on high-impact deals. Flexible Setup Quickly set up incentive compensation plans, adapting to changes in team structure or compensation complexity. Track all plan adjustments with an audit log. Powerful Automation and Workflows Automate complex commission structures, including accelerators, tiers, and triggers. Calculate thousands of statements in seconds to ensure accuracy and efficiency. Seamless Integrations Integrate CRM, ERP, HCM, payroll, or other systems to create a real-time, single source of truth for all commission needs. Data Accuracy Use machine learning to automatically match records, eliminating manual errors and providing a reliable single source of truth. Deep Audit Trail Add effective dates to any user, plan, or logic, and lock historical statements to maintain accuracy. Manage one-off changes without concern. Automated Expense Reporting Maintain compliance under ASC 606 and IFRS 15 with automated, audit-ready expense reports. Use an intuitive interface to manage exceptions, fringe benefits, and varied commission types. Salesforce and Spiff: A Strategic Acquisition After pausing mergers and acquisitions over the past year, Salesforce acquired Spiff at the end of 2023. Previously an AppExchange partner, Spiff provided robust incentive compensation management functionality, calculating commissions for sales based on closed-won deals. Integration into Sales Cloud Salesforce has integrated “Salesforce Spiff” into Sales Cloud, emphasizing the importance of Incentive Compensation Management (ICM) for high-performing companies. With 90% of top-performing companies using incentive programs, this acquisition enhances Salesforce’s offerings. Growth and Market Presence Before the acquisition, Spiff had 1,000 customers and was growing at 100% year-over-year. Salesforce’s market share of approximately 23% in the Sales CRM market indicates significant growth potential for ICM. The Importance of ICM ICM software addresses the complexity of commission calculations, including various percentages for new sales, renewals, bonuses for new customers, accelerators, and team incentives. Accurate calculations across large sales teams are crucial for maintaining motivation and performance. This is a huge time saver. From Excel to Cloud Technology While Excel spreadsheets have been a traditional solution for ICM, Spiff’s cloud technology offers greater functionality and user-friendliness. And it interfaces directly with Sales Cloud. How Salesforce Spiff Works Available as an add-on for Sales Cloud customers from May 2024, Salesforce Spiff offers: Enhanced User Experience The low-code builder simplifies the creation of commission plans, saving time compared to Excel. Real-time commission visibility allows sales users to see potential earnings, motivating them to pursue lucrative opportunities. Final Thoughts Sales roles are essential for driving business revenue. Tools like Spiff provide transparency into potential earnings, significantly impacting sales teams’ motivation and performance. Integrating Spiff into Sales Cloud enhances Salesforce’s value proposition, helping businesses optimize their sales processes and achieve better results. Availability Salesforce Spiff will be available as an add-on for Sales Cloud customers in May 2024. Non-Salesforce customers can also purchase the product from Salesforce.com/salesforcespiff starting May 2024. 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 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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BERT and GPT

BERT and GPT

Breakthroughs in Language Models: From Word2Vec to Transformers Language models have rapidly evolved since 2018, driven by advancements in neural network architectures for text representation. This journey began with Word2Vec and N-Grams in 2013, followed by the emergence of Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks in 2014. The pivotal moment came with the introduction of the Attention Mechanism, which paved the way for large pre-trained models and transformers. BERT and GPT. From Word Embedding to Transformers The story of language models begins with word embedding. What is Word Embedding? Word embedding is a technique in natural language processing (NLP) where words are represented as vectors in a continuous vector space. These vectors capture semantic meanings, allowing words with similar meanings to have similar representations. For instance, in a word embedding model, “king” and “queen” would have vectors close to each other, reflecting their related meanings. Similarly, “car” and “truck” would be near each other, as would “cat” and “dog.” However, “car” and “dog” would not have close vectors due to their different meanings. A notable example of word embedding is Word2Vec. Word2Vec: Neural Network Model Using N-Grams Introduced by Mahajan, Patil, and Sankar in 2013, Word2Vec is a neural network model that uses n-grams by training on context windows of words. It has two main approaches: Both methods help capture semantic relationships, providing meaningful word embeddings that facilitate various NLP tasks like sentiment analysis and machine translation. Recurrent Neural Networks (RNNs) RNNs are designed for sequential data, processing inputs sequentially and maintaining a hidden state that captures information about previous inputs. This makes them suitable for tasks like time series prediction and natural language processing. The concept of RNNs can be traced back to 1925 with the Ising model, used to simulate magnetic interactions analogous to RNNs’ state transitions for sequence learning. Long Short-Term Memory (LSTM) Networks LSTMs, introduced by Hochreiter and Schmidhuber in 1997, are a specialized type of RNN designed to overcome the limitations of standard RNNs, particularly the vanishing gradient problem. They use gates (input, output, and forget gates) to regulate information flow, enabling them to maintain long-term dependencies and remember important information over long sequences. Comparing Word2Vec, RNNs, and LSTMs The Attention Mechanism and Its Impact The attention mechanism, introduced in the paper “Attention Is All You Need” by Vaswani et al., is a key component in transformers and large pre-trained language models. It allows models to focus on specific parts of the input sequence when generating output, assigning different weights to different words or tokens, and enabling the model to prioritize important information and handle long-range dependencies effectively. Transformers: Revolutionizing Language Models Transformers use self-attention mechanisms to process input sequences in parallel, capturing contextual relationships between all tokens in a sequence simultaneously. This improves handling of long-term dependencies and reduces training time. The self-attention mechanism identifies the relevance of each token to every other token within the input sequence, enhancing the model’s ability to understand context. Large Pre-Trained Language Models: BERT and GPT Both BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer) are based on the transformer architecture. BERT Introduced by Google in 2018, BERT pre-trains deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers. This enables BERT to create state-of-the-art models for tasks like question answering and language inference without substantial task-specific architecture modifications. GPT Developed by OpenAI, GPT models are known for generating human-like text. They are pre-trained on large corpora of text and fine-tuned for specific tasks. GPT is majorly generative and unidirectional, focusing on creating new text content like poems, code, scripts, and more. Major Differences Between BERT and GPT In conclusion, while both BERT and GPT are based on the transformer architecture and are pre-trained on large corpora of text, they serve different purposes and excel in different tasks. The advancements from Word2Vec to transformers highlight the rapid evolution of language models, enabling increasingly sophisticated NLP applications. 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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Salesforce Driving Change

Salesforce Driving Change

Sony Honda Mobility Leverages Salesforce Technology to Enhance Customer Relationships Sony Honda Mobility, a mobility tech startup, is utilizing Salesforce solutions—including Automotive Cloud, Data Cloud, Tableau, and MuleSoft—to deepen its customer relationships through enhanced data and insights. Sony Honda Mobility Inc. is a Japanese joint venture automotive company established by Sony Group Corporation and Honda Motor Company in 2022 to produce battery electric vehicles. The company will market its vehicles under the Afeela brand. Why It Matters: A significant 81% of business leaders report challenges with data fragmentation and silos. This disconnected, disjointed information often leads to immaterial and generic customer interactions, which is problematic as 80% of customers expect superior experiences given the extensive data companies collect. Key Developments: Sony Honda Mobility plans to launch its first electric vehicle in the United States in 2025, followed by Japan in 2026. To scale globally and stand out in the market, the company is empowering its service team with real-time data and insights on customer interactions with its products and services. How Is Salesforce Driving Change Data Cloud: A unified data platform that consolidates application, workflow, and data lake records, making it easier to train AI models, gain business insights, and improve customer relationships. Sony Honda Mobility is leveraging Data Cloud to integrate disparate data seamlessly across applications. MuleSoft API Integration: This integration connects data from Sony Honda Mobility’s vehicle and customer platform to Salesforce, ensuring a cohesive data flow. Automotive Cloud: Inside Automotive Cloud, Sony Honda Mobility now maintains a comprehensive profile of each customer and their vehicle, based on data from Data Cloud. This integration allows for personalized service and experiences at every touchpoint. The platform also streamlines contact center management, query handling, internal FAQ creation, web actions, and ongoing service support for incident and customer information management. Tableau: With Tableau’s visualizations of vehicle operation conditions and service usage status, Sony Honda Mobility can make quicker, more informed decisions about each customer’s needs. Customer Perspective “We aim to elevate our customer service and experiences to new heights. We are confident we can achieve this with Salesforce’s global expertise and proven track record in CRM, trusted AI, and data analytics,” said Yasuhide Mizuno, Chairman and CEO of Sony Honda Mobility. Salesforce Perspective “We are thrilled that Sony Honda Mobility has chosen the scalability, reliability, and expertise of Salesforce technology. By integrating their customer data on a single and trusted platform, we are excited to support Sony Honda Mobility as they scale excellent service to customers worldwide,” said Shinichi Koide, Chairman, President, and Chief Executive Officer of Salesforce Japan. The Result By harnessing Salesforce’s advanced technology, Sony Honda Mobility is poised to revolutionize its customer service and experience, ensuring a more connected, efficient, and personalized interaction for its customers globally. 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 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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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 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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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 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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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 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 Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. 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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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 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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