ChatGPT has also appeared in influence operations, with groups using it to generate political content for social media. OpenAI observed an Iranian-led operation, Storm-2035, using ChatGPT to publish politically charged content about U.S. elections and global conflicts. Yet, OpenAI noted that these AI-driven influence efforts often lack audience engagement.
Optimizing your sales commission process through automation can create significant efficiencies, reduce errors, and increase team satisfaction across the organization. Sales commission software provides the real-time data and transparency that today’s sales, finance, and revenue operations (RevOps) teams need to keep pace with business growth. Here are four key benefits of implementing automated commission software: 1. Real-Time Visibility into the Commission Process Sales commission software offers instant access to commission data for reps, managers, and executives. This real-time visibility empowers sales reps to stay focused on high-value deals, knowing their commission data is accurate and transparent. Sales managers can use metrics like quota attainment and earned commissions to track team performance and motivate reps effectively. Automating commission tracking also streamlines end-of-month reporting for finance and RevOps, eliminating the need for manual calculations. And with transparent, accessible data, sales reps can trust the accuracy of their earnings without having to double-check formulas or request manual verifications—freeing them to focus on closing more deals. 2. Increased Productivity Across Teams Manually calculating commissions is both time-consuming and prone to errors, which can erode trust and impact productivity across sales, finance, and RevOps. Automating this process reduces human error and saves teams hours of administrative work, allowing them to redirect energy toward business-critical activities. Manual commission management can also limit scalability; each change in team structure or territory often requires a full recalibration in spreadsheets. With automated software, these adjustments are streamlined, allowing for seamless scalability and supporting growth without adding manual overhead. 3. Improved Accuracy in Commission Calculations Replacing unhappy sales reps is costly, and one common cause of dissatisfaction is inaccurate commission calculations. Studies show nearly 90% of spreadsheets contain errors, and in a process as complex as commission calculation, these errors can lead to mistrust and turnover. Automating commissions removes the risk of errors, helping keep reps happy and reducing friction between sales and finance. A reliable, accurate commission process means reps can trust the data, while finance teams can confidently manage compensation without chasing down mistakes. Few things negatively impact employee focus and loyalty than feeling cheated at payday. 4. Enhanced Access to Data and Actionable Insights Sales commission software does more than calculate earnings—it collects and organizes critical data on sales performance. With these insights, organizations can identify areas for improvement, analyze trends, and optimize their sales strategies. Transform Your Organization with Automated Commission Management Automating your sales commission process isn’t just about efficiency—it’s a powerful way to build trust, enable productivity, and make data-driven decisions that drive growth. By leveraging dedicated incentive compensation management tools, you can empower your teams, reduce operational burdens, and maximize the impact of your sales data. 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
Salesforce’s new Data Cloud One is designed to extend cloud capabilities by allowing multiple departments—or orgs—to collaborate seamlessly on shared data. With Data Cloud One, each department maintains its own CRM and analytics interface, tailored to its specific needs, while accessing a unified database that serves as the single source of truth. The automated exchange of metadata between departments enables efficient, low-code linking and integration. Also within Data Cloud One, multiple Salesforce orgs can be connected and communicate. As your company grows, your business needs grow as well. You might create different Salesforce orgs for different departments, regions, or brands, or inherit them as part of an acquisition. And data about the same customer can end up stored in multiple orgs. It’s great to have all that data, but it’s more valuable if every part of your business can access a single view of each customer. Standard Salesforce CRM connections let you ingest data from many orgs into Data Cloud where it’s unified in the Data Cloud home org. The home org is the primary org where Data Cloud is provisioned and managed. But connected orgs can’t directly access unified data. To make use of unified data in connected orgs, you have to rely on data actions to trigger flows in connected orgs based on the Data Cloud data, or set up complicated custom-coded solutions. Or you have to provision, set up, and maintain a Data Cloud on every org. At the heart of Cloud One is the Home Org, where all data consolidates, and logical units are grouped into Data Spaces. Through automated metadata sharing, other departments (companion orgs) can directly access approved functions within their Cloud One application, creating a standardized network for CRM, data management, analytics, and security. New AI-powered features are also integrated. Role of Salesforce Data Cloud Data Cloud One makes accessing a single Data Cloud across multiple orgs a snap. Orgs connected through a Data Cloud One companion connection are called companion orgs. On top of ingesting data through a standard connection, users in companion orgs also have access to a subset of Data Cloud functionality in the Data Cloud One app. Companion org users can see a complete view of their customers from unified profiles, build custom flows on unified data, directly access calculated insights, and optimize business processes for their use case by powering CRM platform features with Data Cloud. Salesforce Data Cloud One When users set up Data Cloud One, they see a list of Data Spaces available to them. Once authenticated, they gain access to details on shared data, as well as analysis and CRM functionalities. Each user automatically receives three Companion Connections, included in the Salesforce Cloud package, with options to add more as needed. Data Cloud One Architecture In the past, each department worked with its own data set, configurations, users, and security protocols, making inter-departmental data sharing time-consuming and requiring custom code. Data Cloud One simplifies this by allowing companion orgs to connect through a streamlined, automated system, enabling smoother collaboration across departments. Benefits of Data Cloud One When connecting an org to Data Cloud, you can choose between a standard connection and a Data Cloud One companion connection. Let’s compare the access of orgs with each connection. Access Orgs with a Standard Connection Orgs with a Data Cloud One Companion Connection Access to Data Cloud data None Access to Data Cloud metadata, objects, and records in shared data spaces. Data spaces are logical partitions of data within Data Cloud. You can invest in enhanced data security by using Data Cloud data spaces to organize and govern shared data. Access to Data Cloud features None Access to some Data Cloud features in the Data Cloud One app, such as calculated insights and Data Explorer.Access to platform features powered by Data Cloud, such as Flows. Benefits of Data Cloud One Multi-org users of Data Cloud have long sought an easy way to access a unified Customer 360 and take action across multiple orgs. Now, with the general availability of Data Cloud One, that capability has arrived! Data Cloud One equips multiple orgs with a centralized customer profile and Data Cloud-powered features, all accessed through a single, central Data Cloud. This new tool simplifies the onboarding of multi-org teams, transforming how they collaborate within Data Cloud. A Unified Approach to Data Cloud for Multiple Orgs — with Low-Code Configuration So, what is Data Cloud One? It’s a much-anticipated feature designed to enhance multi-org functionality by connecting an entire organization through a single, centralized Data Cloud that serves as the ultimate source of truth. Here’s what Data Cloud One brings to the table: With Data Cloud One, multi-org teams can quickly and seamlessly adopt a comprehensive, shared customer view and Data Cloud-driven capabilities across departments, revolutionizing collaboration and data access. The quest to be data-driven will quickly become the quest to become Data-Cloud driven, and Tectonic is here to help. 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
Informed Decision-Making Through Data Visualization: Power BI vs. Tableau Today’s businesses need to make informed decisions by leveraging organized and analyzed data. Data visualization is a key method for extracting insights from this data, and Power BI and Tableau are two leading tools that often spark debate among experts. Both are highly regarded for their ability to visualize data, and CTOs frequently compare Power BI vs. Tableau to determine the best fit for their needs. Why Power BI and Tableau Stand OutBoth tools excel at data visualization, making them top choices for business intelligence (BI) solutions. They offer seamless integration with various platforms, can handle large volumes of data, and provide predictive analytics capabilities. To help CTOs and other decision-makers boost efficiency, let’s dive into a comparison of Power BI vs. Tableau and examine how each tool measures up. Power BI Microsoft’s Power BI is a leading BI tool designed to transform data from diverse sources into insightful visual reports. It allows users to create, share, and manage analytical reports, ensuring accessibility at all times. As part of the Microsoft ecosystem, Power BI is ideal for large organizations that already use Microsoft products. Tableau Tableau delivers powerful data visualization with flexible deployment options, allowing users to seamlessly access insights. With its integration into Salesforce Data Cloud, Tableau offers a fast and scalable way to work with customer data in real time. Its strong data-handling capabilities make it popular among larger organizations and data experts. Power BI vs. Tableau: Key Differences Let’s explore the key differences between Power BI and Tableau to guide your informed decision-making. Data Visualization and User Interface Data Integration and Connectivity for Informed Decision-Making Data Handling and Performance Ease of Learning Programming Tools Support Pricing Microsoft Power BI vs. Salesforce Tableau: Pros and Cons Power BI Pros Tableau Pros Which is Better: Power BI or Tableau? When comparing Microsoft Power BI vs. Tableau, the right choice depends on your organization’s size, technical expertise, and specific needs. For smaller businesses and those already using Microsoft tools, Power BI is often the best fit. On the other hand, larger organizations managing substantial datasets might favor Tableau for its advanced capabilities. Ultimately, the decision between Power BI vs. Tableau should be based on your unique business requirements and the level of technical expertise available within your team. 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
Sales Incentives That Actually Work Spooktacular Sales incentives to kick off your Halloween. Sales Incentives That Work are an essential tool to encourage and reward desired behaviors within a sales team. They serve as a motivational driver, helping teams achieve their goals while reinforcing the company’s objectives. Incentivizing a team goes beyond merely showing up for work—it involves sparking enthusiasm and a genuine drive to exceed expectations. With the right incentive program, companies can energize their teams, ensuring they come to work motivated and ready to achieve results. Below is a guide on different types of sales incentives, their impact on performance, and best practices for creating an effective incentive program. What Are Sales Incentives? Sales incentives are rewards offered to sales representatives in addition to their base pay for exceptional performance, typically when they meet or exceed sales targets. While monetary rewards such as bonuses are common, sales incentives can take many forms, all aimed at motivating the sales force toward specific goals. Types of Sales Incentives There are five main categories of sales incentives, each tailored to motivate different roles and sales activities: How Sales Incentives Motivate a Team Sales incentives work by reinforcing the behaviors a company wants its team to prioritize. For highly competitive reps, the prospect of a reward adds an extra layer of motivation. For others who may not be as driven by competition, incentives provide tangible goals to strive toward. Moreover, well-structured incentive programs can enhance job satisfaction, decrease turnover, and ensure top performers stay motivated. 10 Effective Sales Incentives While monetary rewards are often the most straightforward incentive, incorporating a mix of creative rewards can enhance a company’s incentive program. Some ideas include: Best Practices for Implementing Sales Incentives A well-designed sales incentive program ensures both clarity and motivation. Some best practices for implementation include: Measuring the Impact of Sales Incentives To gauge the success of a sales incentive program, companies should track key performance indicators (KPIs) like overall sales, new and returning customer numbers, program costs versus ROI, employee turnover, and employee satisfaction. Monitoring these metrics ensures that the program aligns with both sales goals and employee satisfaction. Tectonic’s Final Thoughts Sales incentives are an effective way to drive performance and boost morale. By designing a simple, clear, and motivating incentive program, companies can align their sales goals with individual motivation, ensuring both business success and employee satisfaction. If you need assistance utilizing sales incentives and your Salesforce platform, contact Tectonic today. 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
The Salesforce Maps Winter 25 release will be available in production environments between October 29 – 31. Auto-Enablement of the new Maps experience in October To enhance your experience in Salesforce Maps on desktop, the new features currently available in all environments will be auto-enabled in the Winter ’25 release. The Enhanced User Experience setting in the admin configuration settings will remain and can be manually disabled until the Spring ‘25 release. Get Release Ready-Salesforce Maps Winter 25 To ensure a smooth transition, please take the following actions prior to the production release. What This Change Brings 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
Enterprise interest in artificial intelligence has surged in the past two years, with boardroom discussions centered on how to capitalize on AI advancements before competitors do. Generative AI has been a particular focus for executives since the launch of ChatGPT in November 2022, followed by other major product releases like Amazon’s Bedrock, Google’s Gemini, Meta’s Llama, and a host of SaaS tools incorporating the technology. However, the initial rush driven by fear of missing out (FOMO) is beginning to fade. Business and tech leaders are now shifting their attention from experimentation to more practical concerns: How can AI generate revenue? This question will grow in importance as pilot AI projects move into production, raising expectations for financial returns. Using AI to Increase Revenue AI’s potential to drive revenue will be a critical factor in determining how quickly organizations adopt the technology and how willing they are to invest further. Here are 10 ways businesses can harness AI to boost revenue: 1. Boost Sales AI-powered virtual assistants and chatbots can help increase sales. For example, Ikea’s generative AI tool assists customers in designing their living spaces while shopping for furniture. Similarly, jewelry insurance company BriteCo launched a GenAI chatbot that reduced chat abandonment rates, leading to more successful customer interactions and potentially higher sales. A TechTarget survey revealed that AI-powered customer-facing tools like chatbots are among the top investments for IT leaders. 2. Reduce Customer Churn AI helps businesses retain clients, reducing revenue loss and improving customer lifetime value. By analyzing historical data, AI can profile customer attributes and identify accounts at risk of leaving. AI can then assist in personalizing customer experiences, decreasing churn and fostering loyalty. 3. Enhance Recommendation Engines AI algorithms can analyze customer data to offer personalized product recommendations. This drives cross-selling and upselling opportunities, boosting revenue. For instance, Meta’s AI-powered recommendation engine has increased user engagement across its platforms, attracting more advertisers. 4. Accelerate Marketing Strategies While marketing doesn’t directly generate revenue, it fuels the sales pipeline. Generative AI can quickly produce personalized content, such as newsletters and ads, tailored to customer interests. Gartner predicts that by 2025, 30% of outbound marketing messages will be AI-generated, up from less than 2% in 2022. 5. Detect Fraud AI is instrumental in detecting fraudulent activities, helping businesses preserve revenue. Financial firms like Capital One use machine learning to detect anomalies and prevent credit card fraud, while e-commerce companies leverage AI to flag fraudulent orders. 6. Reinvent Business Processes AI can transform entire business processes, unlocking new revenue streams. For example, Accenture’s 2024 report highlighted an insurance company that expects a 10% revenue boost after retooling its underwriting workflow with AI. In healthcare, AI could streamline revenue cycle management, speeding up reimbursement processes. 7. Develop New Products and Services AI accelerates product development, particularly in industries like pharmaceuticals, where it assists in drug discovery. AI tools also speed up the delivery of digital products, as seen with companies like Ally Financial and ServiceNow, which have reduced software development times by 20% or more. 8. Provide Predictive Maintenance AI-driven predictive maintenance helps prevent costly equipment downtime in industries like manufacturing and fleet management. By identifying equipment on the brink of failure, AI allows companies to schedule repairs and avoid revenue loss from operational disruptions. 9. Improve Forecasting AI’s predictive capabilities enhance planning and forecasting. By analyzing historical and real-time data, AI can predict product demand and customer behavior, enabling businesses to optimize inventory levels and ensure product availability for ready-to-buy customers. 10. Optimize Pricing AI can dynamically adjust prices based on factors like demand shifts and competitor pricing. Reinforcement learning algorithms allow businesses to optimize pricing in real time, ensuring they maximize revenue even as market conditions change. Keeping ROI in Focus While AI offers numerous ways to generate new revenue streams, it also introduces costs in development, infrastructure, and operations—some of which may not be immediately apparent. For instance, research from McKinsey & Company shows that GenAI models account for only 15% of a project’s total cost, with additional expenses related to change management and data preparation often overlooked. To make the most of AI, organizations should prioritize use cases with a clear return on investment (ROI) and postpone those that don’t justify the expense. A focus on ROI ensures that AI deployments align with business goals and contribute to sustainable revenue growth. 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
Google.org Commits $15 Million to AI Training for U.S. Government Workforce Google.org has announced $15 million in grants to support the development of AI skills in the U.S. government workforce, aiming to promote responsible AI use across federal, state, and local levels. These grants, part of Google.org’s broader $75 million AI Opportunity Fund, include $10 million to the Partnership for Public Service and $5 million to InnovateUS. The $10 million grant to the Partnership for Public Service will fund the establishment of the Center for Federal AI, a new hub focused on building AI expertise within the federal government. Set to open in spring 2025, the center will provide a federal AI leadership program, internships, and other initiatives designed to cultivate AI talent in the public sector. InnovateUS will use the $5 million grant to expand AI education for state and local government employees, aiming to train 100,000 workers through specialized courses, workshops, and coaching sessions. “AI is today’s electricity—a transformative technology fundamental to the public sector and society,” said Max Stier, president and CEO of the Partnership for Public Service. “Google.org’s generous support allows us to expand our programming and launch the new Center for Federal AI, empowering agencies to harness AI to better serve the public.” These grants clearly underscore Google.org’s commitment to equipping government agencies with the tools and talent necessary to navigate the evolving AI landscape responsibly. With these tools in place, Tectonic looks forward to assist you in becoming an ai-driven public sector service. 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
Salesforce Introduces Integrated Ecommerce Storefronts in Starter and Pro Suites Salesforce has expanded its Starter and Pro Suites to include integrated ecommerce storefronts, combining capabilities across sales, service, marketing, and now commerce into a seamless, all-in-one solution. This new addition empowers small and growing businesses to create direct-to-consumer (D2C) online stores with ease. Key features include low-code tools for custom storefront design, centralized product and price management, and built-in performance dashboards for insights into customer buying behaviors and store operations. Why This Matters: The shift toward digital commerce continues to grow, with Salesforce research indicating that over half of small business revenue is expected to come from digital channels by 2025, up from 42% today. By packaging ecommerce capabilities directly within its CRM suite, Salesforce aims to simplify digital transformation for businesses and eliminate the need for multiple fragmented solutions. Key Features of Salesforce Ecommerce Storefronts Kris Billmaier, EVP & GM of Self-Service & Growth at Salesforce, emphasized that the suite’s unified data approach will allow businesses to provide a connected experience from purchase to support, stating, “Whether customers buy online, engage with sales teams, or seek help, they will now enjoy a fully integrated journey.” Customer and Salesforce Perspectives Justin Fleming, owner of Clicks N Code, shared his success with the new commerce tools in Pro Suite: “Setting up ecommerce was simple, and my customers can now complete purchases in seconds. The invoicing time reduction from 50 minutes to five has been a game-changer.” According to Salesforce, the integration of ecommerce within the CRM suite will help businesses sell more efficiently and improve customer experiences by unifying data and simplifying operations. By Tectonic’s Marketing Ops Director, Shannan Hearne Like2 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
Generative AI has far more to offer your site than simply mimicking a conversational ChatGPT-like experience or providing features like generating cover letters on resume sites. Let’s explore how you can integrate Generative AI with your product in diverse and innovative ways! There are three key perspectives to consider when integrating Generative AI with your features: system scope, spatial relationship, and functional relationship. Each perspective offers a different lens for exploring integration pathways and can spark valuable conversations about melding AI with your product ecosystem. These categories aren’t mutually exclusive; instead, they overlap and provide flexible ways of envisioning AI’s role. 1. System Scope — The Reach of Generative AI in Your System System scope refers to the breadth of integration within your system. By viewing integration from this angle, you can assess the role AI plays in managing your platform’s overall functionality. While these categories may overlap, they are useful in facilitating strategic conversations. 2. Spatial Relationships — Where AI Interacts with Features Spatial relationships describe where AI features sit in relation to your platform’s functionality: 3. Functional Relationships — How AI Interacts with Features Functional relationships determine how AI and platform features work together. This includes how users engage with AI and how AI content updates based on feature interactions: Scope of Generative AI By considering these different perspectives—system scope, spatial, and functional—you can drive more meaningful conversations about how Generative AI can best enhance your product’s capabilities. Each approach offers unique value, and careful thought can help teams choose the integration path that aligns with their needs and goals. Scope of Generative AI conversations with Tectonic can assist in planning the best ROI approach to AI. Contact us today. 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
AI Pitchfield is more than a showcase of entrepreneurial talent—it’s a launchpad for the next generation of AI pioneers. By fostering connections and providing critical investment opportunities, Salesforce and its partners are driving the evolution of AI across India and Southeast Asia. This initiative reflects Salesforce’s commitment to advancing technology, empowering startups, and shaping a future where AI continues to transform industries and unlock untapped potential.
Large Language Models (LLMs): Revolutionizing AI and Custom Solutions Large Language Models (LLMs) are transforming artificial intelligence by enabling machines to generate and comprehend human-like text, making them indispensable across numerous industries. The global LLM market is experiencing explosive growth, projected to rise from $1.59 billion in 2023 to $259.8 billion by 2030. This surge is driven by the increasing demand for automated content creation, advances in AI technology, and the need for improved human-machine communication. Several factors are propelling this growth, including advancements in AI and Natural Language Processing (NLP), large datasets, and the rising importance of seamless human-machine interaction. Additionally, private LLMs are gaining traction as businesses seek more control over their data and customization. These private models provide tailored solutions, reduce dependency on third-party providers, and enhance data privacy. This guide will walk you through building your own private LLM, offering valuable insights for both newcomers and seasoned professionals. What are Large Language Models? Large Language Models (LLMs) are advanced AI systems that generate human-like text by processing vast amounts of data using sophisticated neural networks, such as transformers. These models excel in tasks such as content creation, language translation, question answering, and conversation, making them valuable across industries, from customer service to data analysis. LLMs are generally classified into three types: LLMs learn language rules by analyzing vast text datasets, similar to how reading numerous books helps someone understand a language. Once trained, these models can generate content, answer questions, and engage in meaningful conversations. For example, an LLM can write a story about a space mission based on knowledge gained from reading space adventure stories, or it can explain photosynthesis using information drawn from biology texts. Building a Private LLM Data Curation for LLMs Recent LLMs, such as Llama 3 and GPT-4, are trained on massive datasets—Llama 3 on 15 trillion tokens and GPT-4 on 6.5 trillion tokens. These datasets are drawn from diverse sources, including social media (140 trillion tokens), academic texts, and private data, with sizes ranging from hundreds of terabytes to multiple petabytes. This breadth of training enables LLMs to develop a deep understanding of language, covering diverse patterns, vocabularies, and contexts. Common data sources for LLMs include: Data Preprocessing After data collection, the data must be cleaned and structured. Key steps include: LLM Training Loop Key training stages include: Evaluating Your LLM After training, it is crucial to assess the LLM’s performance using industry-standard benchmarks: When fine-tuning LLMs for specific applications, tailor your evaluation metrics to the task. For instance, in healthcare, matching disease descriptions with appropriate codes may be a top priority. Conclusion Building a private LLM provides unmatched customization, enhanced data privacy, and optimized performance. From data curation to model evaluation, this guide has outlined the essential steps to create an LLM tailored to your specific needs. Whether you’re just starting or seeking to refine your skills, building a private LLM can empower your organization with state-of-the-art AI capabilities. For expert guidance or to kickstart your LLM journey, feel free to contact us for a free consultation. 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
Best Practices for Safely Deploying Salesforce Einstein Copilot When deploying Salesforce Einstein Copilot, following best practices ensures a secure, efficient, and effective integration of AI into your workflows. Here are the key steps to safely deploy Einstein Copilot: By adhering to these best practices, you can ensure a smooth, secure, and successful deployment of Salesforce Einstein Copilot, enhancing your team’s productivity while maintaining data integrity and security. 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
Salesforce CEO Marc Benioff recently critiqued Microsoft for overhyping the capabilities of its Copilot AI tool, arguing that the tech giant has done a “tremendous disservice” to the industry. In a Rapid Response interview with Bob Safian, Benioff emphasized that Salesforce’s Agentforce is “what AI was meant to be.” More excited than ever, he sees Agentforce as a technology poised to transform industries in ways comparable to past cloud, mobile, and social revolutions. Benioff Excited About AI. Reflecting on Dreamforce 2024Benioff called this year’s Dreamforce the most significant yet. With 45,000 attendees and millions joining online, Agentforce took center stage, allowing users to build their own AI agents firsthand. This hands-on experience was vital, he said, to clear up misconceptions caused by overpromised AI products. Salesforce already handles trillions of AI transactions through its Einstein platform, but Benioff believes Agentforce represents a groundbreaking shift in enterprise AI. Agentforce vs. Copilot: A Clear DifferenceBenioff drew a sharp contrast between Agentforce and Microsoft’s Copilot, comparing the latter to the infamous Microsoft Clippy. According to Benioff, Copilot often fails to deliver meaningful results, creating confusion and dissatisfaction among customers. In contrast, Agentforce is set to deliver powerful outcomes by connecting customers, raising revenues, and augmenting employees. He anticipates that within a year, Salesforce will operate over a billion AI agents worldwide. Benioff Excited About AI. Benioff Excited About AI Agentforce’s Real-World ImpactSharing a story from the healthcare sector, Benioff illustrated how Agentforce has resolved over 90% of patient inquiries and scheduling needs for one large provider, enabling rapid and meaningful interactions. He foresees similar applications across media, finance, and travel, as Agentforce helps industries implement AI-driven agents with high success rates. Scheduled to go live on October 25, Agentforce is expected to be adopted by hundreds of thousands of companies. MIT IDE Annual Conference Insights: AI’s Potential and ChallengesWhile businesses explore AI’s possibilities, researchers at MIT’s Initiative on the Digital Economy (IDE) are investigating the complexities and ethical considerations of AI. At the 2024 MIT IDE Annual Conference, findings on AI’s influence on various domains were presented, with highlights including: These MIT findings highlight both the immense promise and the challenges AI presents, as companies like Salesforce aim to harness AI’s true potential while navigating ethical and practical concerns. 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
In need of help to implement requisite configuration updates to establish a usable data model for data segmentation that supports best practices utilization of Marketing Cloud features including Contact Builder, Email Studio and Journey Builder.
