Salesforce Einstein Archives - gettectonic.com - Page 5

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Salesforce AI Journey

Salesforce AI Journey

“We’re on an Incredible Journey”: Why Salesforce’s AI Push is Just Beginning This article originally appeared in TechRadar by Mike Moore. Salesforce AI Journey. When it comes to leveraging AI to enhance global workforces, some companies are leading the charge, particularly when their technology is at the forefront. Salesforce, known for its robust AI tools, is one such company pushing the boundaries. At its recent World Tour London event, Salesforce emphasized its commitment to AI, showcasing how its Einstein tools are already benefiting customers worldwide. TechRadar Pro spoke with Paul O’Sullivan, SVP, Solution Engineering & UKI, CTO, Salesforce, about the company’s vision for enhancing efficiency and productivity across all markets, particularly in the UK. A Wave of Innovation “We’re on an incredible journey,” O’Sullivan stated, referencing Salesforce’s $4 billion investment in the UK and Ireland in 2023. “We’re well-positioned in the UK to maximize AI’s potential and help our customers achieve true value.” This ambition is epitomized by Salesforce’s new AI center in London. The 40,000 square foot facility is set to be a hub for AI collaboration and development, addressing the growing demand for AI technology. O’Sullivan hinted that this is just the beginning. “We’re an innovation-led company—always looking ahead,” he said, highlighting the UK’s history of driving innovation as a positive indicator for AI’s future in the capital. Growing Demand and Education As demand for AI tools and services increases among businesses of all sizes, O’Sullivan acknowledged the rapid pace of change in the AI landscape. “It starts with education—at all levels,” he noted, recognizing the varying degrees of AI knowledge among business leaders. O’Sullivan compared the current AI momentum to past technological revolutions like cloud computing, websites, and ecommerce. Companies had to adapt quickly to avoid falling behind, and he noted that the window for catching up with AI might be even smaller. He predicted a “steady wave of innovation” in AI before it becomes ubiquitous in the business world, with various models and platforms vying for dominance. “It feels like everyone is in a race for AI,” he added, “and there’s a collective agreement that AI will enhance productivity and efficiency, benefiting both the bottom and top lines of big enterprises.” Human Jobs and AI Looking forward, O’Sullivan dismissed concerns that AI would replace human jobs. He suggested that AI would instead create new opportunities for human workers. “I think human nature is inherently curious,” he said. “We will continue to explore new ways of doing things and offer different levels of connection and service.” Drawing parallels to the industrial revolution, O’Sullivan pointed out that machines didn’t eliminate jobs; they increased productivity and efficiency. He believes AI will have a similar impact. “We’re going to see a new level of productivity and efficiency with AI, just as we did with the industrial revolution,” he concluded. Salesforce’s AI journey is only just beginning, promising exciting advancements and opportunities for businesses and workers alike. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Summer 24 Release Updates

Summer 24 Release Updates

Salesforce’s Summer 24 release updates are designed to help teams work more efficiently with innovations in data, AI, CRM, and trust. These updates aim to save businesses time and enhance the end-user experience with improved search results, personalized experiences, and more. Highlights of Salesforce’s Summer 2024 Updates Activate and Publish a Store Without a Custom Domain Previously, B2B Commerce Lightning Web Runtime (LWR) required purchasing and configuring a custom CDN domain to log in to the storefront, even for demo purposes. Now, users can activate and view the storefront before setting up a custom domain, saving both time and costs. The custom domain and CDN can be configured when ready to go live. Include Attachments When Importing Products Adding attachments to products during import was a manual and time-consuming process. Now, users can include document URLs in the CSV file during product data import, consolidating vital product information and reducing the potential for human error. Implement Einstein Semantic Search Highlighted again from the Spring 2024 release, Einstein Semantic Search is crucial for commerce. It improves search relevance, reduces bounce rates, and increases conversion rates by recognizing synonyms, alternate spellings, abbreviations, typos, and more. Integrate Data Cloud with Enhanced LWR Sites In the context of walled gardens and cookie deprecation, using owned data is critical for future readiness and better customer experiences. Integrating Data Cloud with enhanced LWR sites allows for the collection of user data, such as profile information and site engagement. This data builds user profiles, creates analytics, suggests personalized recommendations, and enhances site personalization. See a Summary of a User’s Permissions and Access Previously, viewing a user’s permissions required multiple clicks and accessing various locations. The new User Access Summary feature displays all permissions directly on the user‘s detail page, streamlining the troubleshooting and access management process. These enhancements in Salesforce’s Summer 2024 release are aimed at improving efficiency, personalization, and user experience, helping businesses to operate smarter and more effectively. Summer 24 Release Updates summarized for you. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Flow Tricks for Salesforce

Flow Tricks for Salesforce

Flow enthusiasts everywhere appreciate its capabilities, which continue to evolve as a cornerstone of Salesforce declarative automation. Here are five essential Flow Tricks for Salesforce: In conclusion, embracing Flow not only optimizes business processes but also fosters continuous learning and improvement. By sharing insights and best practices, the Flow community collectively enhances user experiences and drives innovation. Whether you’re new to Flow or a seasoned user, these tips aim to enhance your journey and empower you to explore further possibilities. Share your own tips and experiences below to continue the Flow journey together! Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Generative AI Regulations

AI Manipulation

The Future of AI: Convenience and Risk Our lives are on the brink of being transformed by conversational AI agents designed to anticipate our needs, offer tailored information, and perform useful tasks on our behalf. These agents will rely on extensive personal data, including our interests, hobbies, backgrounds, aspirations, personality traits, and political views, all aimed at making our lives more convenient. What then will be the source of AI Manipulation? Advanced AI Agents: The Next Generation These AI agents are becoming increasingly sophisticated. OpenAI recently released GPT-4o, a next-generation chatbot capable of reading human emotions. It does this not only by analyzing the sentiment in written text but also by assessing voice inflections (if spoken to through a mic) and facial cues (if interacting via video). This rapid development signifies the future of computing. Google, for instance, announced Project Astra, an advanced seeing and talking responsive agent designed to interact conversationally while understanding its surroundings. This allows it to provide real-time interactive guidance and assistance. OpenAI’s Sam Altman has predicted that assistive agents will be the killer app for AI. He envisions a future where everyone has a personalized agent acting as a super-competent colleague, knowing everything about their life to take useful actions on their behalf. The Potential Risks-AI Manipulation While this sounds promising, significant risks accompany these advancements. As I wrote in VentureBeat last year, AI agents pose a risk to human agency through targeted manipulation. This risk is particularly acute as these agents become embedded in our mobile devices, which are gateways to our digital lives. These devices provide AI agents with a continuous flow of our personal information, enabling them to learn intimate details about us while filtering the content we receive. Such systems could become powerful tools for interactive manipulation. AI agents equipped with cameras and microphones will react to our environments without explicit prompts, potentially triggering targeted influences based on our activities and situations. Public Perception and Adoption Despite the creepy level of tracking and intervention, I predict that people will embrace this technology. These agents will be designed to make our lives easier, providing reminders, tutoring, and even social coaching. The competition among tech companies will drive rapid adoption, with individuals feeling disadvantaged if they do not use these features. By 2030, these technologies will likely be ubiquitous. The AI Manipulation Problem In my new book, “Our Next Reality,” I discuss how AI agents can empower us with mental superpowers while also serving as tools for persuasion. AI agents, designed for profit, will influence our thoughts and behaviors. They will be more effective than traditional content because they can engage us interactively, using sophisticated techniques based on extensive personal data. These agents will read our emotions with unparalleled precision, adapting their influence tactics in real-time. Without regulation, they could document our reactions to tailor their approaches, making them highly effective at persuasion. The agents’ appearances could also be optimized to maximize their impact on us personally. Feedback Control and the Need for Regulation The technical danger of AI agents lies in their feedback control capabilities. Given an “influence objective,” these agents can continuously adapt their strategies to maximize their impact on us. This ability is similar to heat-seeking missiles adjusting their path in real-time to hit a target. To mitigate this risk, regulators must impose strict limits on interactive conversational advertising, which is the gateway to more dangerous uses of these technologies. If unchecked, this could lead to an arms race among tech companies to develop the most effective conversational ads, ultimately driving misinformation and propaganda. The Urgent Need for Regulatory Action The time for policymakers to act is now. While traditional AI risks like generating misinformation at scale are significant, targeted interactive manipulation poses a far greater threat. Recent announcements from OpenAI and Google highlight the urgency for regulation. An outright ban or stringent limitations on interactive conversational advertising is a crucial first step. Without such measures, we risk allowing AI agents to become powerful tools of manipulation. Conclusion The future of AI holds both promise and peril. As conversational AI agents become integral to our daily lives, we must balance their benefits with the potential for abuse. Regulatory action is essential to ensure these technologies enhance our lives without compromising our autonomy. Louis Rosenberg, PhD, is an American technologist specializing in AI and XR. His new book, “Our Next Reality,” explores the impact of AI on society and is published by Hachette. He earned his PhD from Stanford, was a professor at California Polytechnic, and is currently CEO of Unanimous AI. This piece originally appeared in VentureBeat on 5/17/24. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Slack Integrating AI Into Platform

Slack Integrating AI Into Platform

Slack’s CEO Denise Dresser announced that AI will soon be integrated into every aspect of the platform, enabling users to manage tasks and launch new projects without leaving the application. This announcement highlights a significant shift towards enhancing productivity and collaboration within Slack using advanced AI capabilities. Slack Integrating AI Into Platform. During a media session following her keynote at Salesforce’s World Tour event in Boston, Dresser outlined her vision for AI in Slack. Having taken on her role six months ago after years with Salesforce, she emphasized the integration of Slack with Salesforce’s Einstein Copilot. Acquired by Salesforce in late 2020, Slack aims to provide a unified experience for users by leveraging AI to manage both structured and unstructured data. The goal is to help users quickly find key conversations and turn them into actionable tasks and projects. Dresser noted the challenges in navigating chat histories and identifying important moments, which AI integration aims to address. Slack Integrating AI Into Platform “AI can significantly drive productivity,” Dresser said. “With Slack AI Search, Slack becomes your organization’s long-term memory. It allows users to easily find what they need through generative summaries, which was a major breakthrough for us.” Dresser highlighted the rapid adoption of AI and its integration into Slack’s functionality, leading to an evolution in skills such as prompt engineering and natural language processing. These advancements enable tasks like software creation without traditional coding methods. She pointed out the rapid growth in AI adoption, comparing it to the adoption rates of ChatGPT, mobile phones, and Facebook. Dresser believes this trend will continue as people experience productivity improvements with AI. AI will be embedded in various Slack features, including Canvas, Workflow, and Huddle, providing seamless assistance within the application. Users may not even realize they are interacting with AI, as it will naturally enhance Slack’s functionality. For instance, instead of manually searching through messages, AI will highlight the most important summaries. Dresser also mentioned the newly launched Slack Lists feature, which automatically captures and surfaces key parts of channel conversations. She stressed the importance of reducing the need to switch between different applications, which can drain time and productivity. “We have millions of people working in Slack; why leave Slack?” she said. “We wanted to integrate capabilities for tasks, lists, and projects directly into Slack, starting right within conversations.” In the future, Slack will also suggest relevant chat channels for project purposes, providing users with powerful insights and capabilities. Dresser noted that while only about a third of employees currently use AI-powered platforms, those who do report an average 81% increase in productivity by eliminating mundane tasks. As AI continues to be embedded into Slack and Salesforce tools, Dresser acknowledged the challenge of maintaining the platform’s beloved feel and integrity. “We’ve already integrated Slack, Sales Elevate, and Salesforce. Copilot’s integration will be excellent,” she said. “We have focused on preserving the unique Slack experience, even while enhancing it with new architectural integrations. Our goal is to ensure that Slack remains efficient and productive while staying true to its core identity.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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DPD Salesforce AI Enhancements

DPD Salesforce AI Enhancements

DPD’s AI Integration: Enhancing Customer and Employee Experience DPD has ambitious plans to integrate AI throughout its Salesforce platform, aiming to automate tasks and significantly enhance the experiences of both customers and employees. DPD Salesforce AI Enhancements. Adam Hooper, Head of Central Platforms at DPD, explains that with over 400 million parcels delivered annually, maintaining robust customer relationships is crucial. To this end, DPD leverages a range of Salesforce technologies, including Service Cloud, Sales Cloud, Marketing Cloud, and Mulesoft. AI-Powered Customer Service In Salesforce’s latest update on DPD: Financial and Operational Efficiency Targeted Marketing Spreadsheets to Salesforce At the Salesforce World Tour event in London, Ben Pyne, Salesforce Platform Manager at DPD, elaborated on their current usage and future AI plans. Pyne’s team acts as internal consultants to optimize organizational workflows. As he explains: “My role is essentially to get people off spreadsheets and onto Salesforce!” He noted that about 40 departments and teams within DPD use Salesforce, far beyond the typical Sales and CRM applications. Custom applications within Salesforce personalize and enhance user experiences by focusing on relevant information. Using tools like Prompt Builder, Pyne’s team recently developed a project management app within Salesforce, streamlining tasks like writing acceptance criteria and user stories. Pyne emphasized: “I want our guys to focus on designing and building, less on the admin.” AI Use Cases When considering AI and generative AI, DPD sees significant potential to reduce operational tasks. Pyne highlighted case summarization as an obvious application, given the millions of customer service cases created each year. Rolling Out Generative AI DPD adopts a cautious approach to rolling out new technologies like generative AI. Pyne explained: “It’s starting small, finding the right teams to be able to do it. But fundamentally, starting somewhere and making slow progressions into it to ensure we don’t scare everybody away.” Ensuring Security and Trust Security and trust are paramount for DPD. Pyne noted their robust IT security team scrutinizes every implementation. Fortunately, Salesforce’s security measures, such as data anonymization and preventing LLMs (Large Language Models) from learning from their data, provide peace of mind. Pyne concluded: “We can focus on what we’re good at and not worry about the rest because Salesforce has thought of everything for us.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Salesforce Feeding Post-Pandemic AI-Powered Digital Transformation

Salesforce Feeding Post-Pandemic AI-Powered Digital Transformation

The Digital Transformation Imperative: Salesforce’s AI Solutions The COVID-19 pandemic didn’t just accelerate digital transformation; it cemented it as an existential imperative for businesses across all industries. The sudden shift to remote work, digital customer engagement, and e-commerce highlighted the stark contrast between organizations that had prioritized digitization and those that hadn’t. In the post-pandemic era, digital agility has become synonymous with resilience and competitiveness. Salesforce Feeding Post-Pandemic AI-Powered Digital Transformation with unparalled innovation. However, the path to digital transformation remains challenging for many companies. Legacy systems, data silos, and manual processes continue to hinder adaptation and innovation at the pace demanded by today’s market and consumer. This has led to a certain weariness and skepticism around transformation initiatives, often perceived as an ever-receding target. Salesforce’s AI-Powered Integration Solutions Salesforce’s AI-powered integration solutions aim to revitalize the digital transformation journey. With tools like Einstein for Flow, Intelligent Document Processing (IDP), and Einstein for MuleSoft, Salesforce is embedding AI across its automation and integration portfolio to address some of the most difficult challenges in digitization. Anypoint Partner Manager: Harnessing AI for B2B Integration Salesforce’s latest MuleSoft offering, Anypoint Partner Manager, exemplifies this AI-centric approach. The cloud-native B2B integration solution leverages IDP to streamline partner onboarding and manage API and EDI-based transactions, addressing a key pain point for companies in complex supply chain ecosystems. “EDI has historically been that code-driven solution. You must really know the EDI spec,” noted Andrew Comstock, VP of Product Management at Salesforce. “Partner Manager actually brings the partner definition into a form, and you can just define that, save it, and you’re off and done. We can deploy all the applications that you need for you.” By using AI to extract and structure data from unstructured documents like invoices and purchase orders, Anypoint Partner Manager democratizes B2B integration, making it accessible to businesses beyond the traditional technology sector. The solution is now generally available. MuleSoft Accelerator for Salesforce Order Management: Bridging B2B and B2C Salesforce also introduced the MuleSoft Accelerator for Salesforce Order Management. This tool provides pre-built APIs, connectors, and templates to unify B2B and B2C orders from a centralized hub. By connecting Salesforce OMS with ERP systems in real-time, the accelerator enables end-to-end visibility across channels, a critical capability in today’s omnichannel environment. “For many companies, [order management] is super critical and vital,” emphasized Comstock. “The more that they can standardize and centralize that, the better visibility, controls, and governance they have.” The MuleSoft Accelerator for Salesforce OMS is now generally available. The AI Imperative in Digital Transformation Salesforce’s AI-powered integration solutions come at a time when businesses are grappling with the realities of the post-pandemic digital imperative. Automating complex B2B processes, unifying data flows across ecosystems, and extracting insights from unstructured data is no longer a luxury but a necessity for survival in the digital economy. Salesforce Feeding Post-Pandemic AI-Powered Digital Transformation “A lot of our successes are happening at companies that are not traditional technology companies. Using solutions like MuleSoft and Salesforce allows them to build those technologies better,” noted Comstock. In this context, AI is emerging as a key enabler of digital transformation at scale. By abstracting complexity and automating manual tasks, AI-powered integration tools like those from Salesforce are helping businesses overcome the hurdles that have long stymied digitization efforts. For companies still wrestling with the challenges of digital transformation, Salesforce’s AI-powered integration portfolio offers a glimmer of hope. By harnessing the power of large language models and other AI technologies to streamline integration and automation, Salesforce is providing a new path forward for organizations looking to thrive in the post-pandemic digital landscape. Salesforce Feeding Post-Pandemic AI-Powered Digital Transformation with Einstein, Mulesoft, Flow, and more. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Databricks LakeFlow

Databricks LakeFlow

Databricks Introduces LakeFlow: Simplifying Data Engineering Databricks, the Data and AI company, yesterday announced the launch of Databricks LakeFlow, a new solution designed to unify and simplify all aspects of data engineering, from data ingestion to transformation and orchestration. LakeFlow enables data teams to efficiently ingest data at scale from databases like MySQL, Postgres, and Oracle, as well as enterprise applications such as Salesforce, Dynamics, SharePoint, Workday, NetSuite, and Google Analytics. Additionally, Databricks is introducing Real Time Mode for Apache Spark, allowing ultra-low latency stream processing. Simplified Data Engineering with LakeFlow LakeFlow automates the deployment, operation, and monitoring of data pipelines at scale, with built-in support for CI/CD and advanced workflows that include triggering, branching, and conditional execution. It integrates data quality checks and health monitoring with alerting systems such as PagerDuty, simplifying the process of building and operating production-grade data pipelines. This efficiency enables data teams to meet the growing demand for reliable data and AI. Tackling Data Pipeline Challenges Data engineering is crucial for democratizing data and AI within businesses but remains complex and challenging. Data teams often struggle with ingesting data from siloed, proprietary systems, and managing intricate logic for data preparation. Failures and latency spikes can disrupt operations and disappoint customers. The deployment of pipelines and monitoring of data quality typically involve disparate tools, complicating the process further. Fragmented solutions lead to low data quality, reliability issues, high costs, and increasing backlogs. LakeFlow addresses these challenges by providing a unified experience on the Databricks Data Intelligence Platform, with deep integrations with Unity Catalog for end-to-end governance and serverless compute for efficient and scalable execution. Key Features of LakeFlow Availability LakeFlow represents the future of unified and intelligent data engineering. The preview phase will begin soon, starting with LakeFlow Connect. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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Adopt a Large Language Model

Adopt a Large Language Model

In 2023, Algo Communications, a Canadian company, faced a significant challenge. With rapid growth on the horizon, the company struggled to train customer service representatives (CSRs) quickly enough to keep pace. To address this, Algo turned to an innovative solution: generative AI. They needed to Adopt a Large Language Model. Algo adopted a large language model (LLM) to accelerate the onboarding of new CSRs. However, to ensure CSRs could accurately and fluently respond to complex customer queries, Algo needed more than a generic, off-the-shelf LLM. These models, typically trained on public internet data, lack the specific business context required for accurate answers. This led Algo to use retrieval-augmented generation, or RAG. Many people have already used generative AI models like OpenAI’s ChatGPT or Google’s Gemini (formerly Bard) for tasks like writing emails or crafting social media posts. However, achieving the best results can be challenging without mastering the art of crafting precise prompts. An AI model is only as effective as the data it’s trained on. For optimal performance, it needs accurate, contextual information rather than generic data. Off-the-shelf LLMs often lack up-to-date, reliable access to your specific data and customer relationships. RAG addresses this by embedding the most current and relevant proprietary data directly into LLM prompts. RAG isn’t limited to structured data like spreadsheets or relational databases. It can retrieve all types of data, including unstructured data such as emails, PDFs, chat logs, and social media posts, enhancing the AI’s output quality. How RAG Works RAG enables companies to retrieve and utilize data from various internal sources for improved AI results. By using your own trusted data, RAG reduces or eliminates hallucinations and incorrect outputs, ensuring responses are relevant and accurate. This process involves a specialized database called a vector database, which stores data in a numerical format suitable for AI and retrieves it when prompted. “RAG can’t do its job without the vector database doing its job,” said Ryan Schellack, Director of AI Product Marketing at Salesforce. “The two go hand in hand. Supporting retrieval-augmented generation means supporting a vector store and a machine-learning search mechanism designed for that data.” RAG, combined with a vector database, significantly enhances LLM outputs. However, users still need to understand the basics of crafting clear prompts. Faster Responses to Complex Questions In December 2023, Algo Communications began testing RAG with a few CSRs using a small sample of about 10% of its product base. They incorporated vast amounts of unstructured data, including chat logs and two years of email history, into their vector database. After about two months, CSRs became comfortable with the tool, leading to a wider rollout. In just two months, Algo’s customer service team improved case resolution times by 67%, allowing them to handle new inquiries more efficiently. “Exploring RAG helped us understand we could integrate much more data,” said Ryan Zoehner, Vice President of Commercial Operations at Algo Communications. “It enabled us to provide detailed, technically savvy responses, enhancing customer confidence.” RAG now touches 60% of Algo’s products and continues to expand. The company is continually adding new chat logs and conversations to the database, further enriching the AI’s contextual understanding. This approach has halved onboarding time, supporting Algo’s rapid growth. “RAG is making us more efficient,” Zoehner said. “It enhances job satisfaction and speeds up onboarding. Unlike other LLM efforts, RAG lets us maintain our brand identity and company ethos.” RAG has also allowed Algo’s CSRs to focus more on personalizing customer interactions. “It allows our team to ensure responses resonate well,” Zoehner said. “This human touch aligns with our brand and ensures quality across all interactions.” Write Better Prompts – Adopt a Large Language Model If you want to learn how to craft effective generative AI prompts or use Salesforce’s Prompt Builder, check out Trailhead, Salesforce’s free online learning platform. Start learning Trail: Get Started with Prompts and Prompt Builder Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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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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Gen AI Unleased With Vector Database

Gen AI Unleased With Vector Database

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

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ChatGPT 5.0 is Coming

ChatGPT 5.0 is Coming

Sam Altman Teases ChatGPT-5: Here’s What We Know GPT-5: A Major Leap in AI Following the release of GPT-4, anticipation for its successor, GPT-5, has been growing. According to reports from Business Insider, GPT-5 is expected to debut in mid-2024, potentially marking a significant advancement in AI capabilities. Insiders describe GPT-5 as “materially better,” with enhancements that could transform AI-driven communication and composition. ChatGPT 5.0 is Coming. The Journey to GPT-5 After GPT-4’s launch, speculation about GPT-5’s arrival intensified. OpenAI CEO Sam Altman has hinted at the upcoming release, assuring groundbreaking advancements. However, concrete details were scarce until recent reports provided a clearer timeline for GPT-5’s debut. What to Expect from GPT-5 Early demonstrations of GPT-5 have impressed insiders, with one CEO describing it as “really good.” The model promises significant improvements, showcasing its versatility in real-world applications. From unique use cases for individual enterprises to autonomous AI agents, GPT-5 is poised to expand the boundaries of AI capabilities. Evolution of Language Models Understanding GPT-5’s significance involves tracing the evolution of OpenAI’s language models. From the groundbreaking GPT-3 in 2020 to the iterative improvements leading to GPT-4 Turbo, each iteration has advanced the sophistication of AI-driven communication tools. ChatGPT 5.0 is Coming: A Multimodal Approach Building on its predecessors, GPT-5 is expected to offer a multimodal experience, integrating text and encoded visual input. This capability opens up numerous applications, from content generation to image captioning, further embedding AI in various domains. Next-Token Prediction and Conversational AI At its core, GPT-5 remains a next-token prediction model, generating contextually relevant responses based on input prompts. This functionality underpins conversational AI applications like ChatGPT, enabling seamless user-AI interactions. Challenges and Opportunities Ahead As OpenAI prepares for GPT-5’s launch, the focus shifts to the challenges and opportunities it presents. Addressing concerns about model performance and reliability, and exploring novel use cases, the journey towards realizing the full potential of AI-driven language models is filled with possibilities. Ensuring Safety and Reliability Ensuring the success of GPT-5 involves rigorous testing and validation to guarantee its safety and reliability. As AI continues to advance, maintaining transparency and accountability in its development is crucial. Unlocking New Frontiers Beyond immediate applications, GPT-5 represents a significant step towards unlocking new frontiers in AI innovation. From enhancing natural language understanding to facilitating human-machine collaboration, the implications of GPT-5 extend far beyond its initial release. 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 Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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GPT-4o GPT4 and Gemini 1.5

GPT-4o GPT4 and Gemini 1.5

An Independent Analysis of GPT-4o’s Classification Abilities Article by Lars Wilk OpenAI’s recent unveiling of GPT-4o marks a significant advancement in AI language models, transforming how we interact with them. The most impressive feature is the live interaction capability with ChatGPT, allowing for seamless conversational interruptions. GPT-4o GPT4 and Gemini 1.5 Despite a few hiccups during the live demo, the achievements of the OpenAI team are undeniably impressive. Best of all, immediately after the demo, OpenAI granted access to the GPT-4o API. In this article, I will present my independent analysis, comparing the classification abilities of GPT-4o with GPT-4, Google’s Gemini, and Unicorn models using an English dataset I created. Which of these models is the strongest in understanding English? What’s New with GPT-4o? GPT-4o introduces the concept of an Omni model, designed to seamlessly process text, audio, and video. OpenAI aims to democratize GPT-4 level intelligence, making it accessible even to free users. Enhanced quality and speed across more than 50 languages, combined with a lower price point, promise a more inclusive and globally accessible AI experience. Additionally, paid subscribers will benefit from five times the capacity compared to non-paid users. OpenAI also announced a desktop version of ChatGPT to facilitate real-time reasoning across audio, vision, and text interfaces. How to Use the GPT-4o API The new GPT-4o model follows the existing chat-completion API, ensuring backward compatibility and ease of use: pythonCopy codefrom openai import AsyncOpenAI OPENAI_API_KEY = “<your-api-key>” def openai_chat_resolve(response: dict, strip_tokens=None) -> str: if strip_tokens is None: strip_tokens = [] if response and response.choices and len(response.choices) > 0: content = response.choices[0].message.content.strip() if content: for token in strip_tokens: content = content.replace(token, ”) return content raise Exception(f’Cannot resolve response: {response}’) async def openai_chat_request(prompt: str, model_name: str, temperature=0.0): message = {‘role’: ‘user’, ‘content’: prompt} client = AsyncOpenAI(api_key=OPENAI_API_KEY) return await client.chat.completions.create( model=model_name, messages=[message], temperature=temperature, ) openai_chat_request(prompt=”Hello!”, model_name=”gpt-4o-2024-05-13″) GPT-4o is also accessible via the ChatGPT interface. Official Evaluation GPT-4o GPT4 and Gemini 1.5 OpenAI’s blog post includes evaluation scores on known datasets such as MMLU and HumanEval, showcasing GPT-4o’s state-of-the-art performance. However, many models claim superior performance on open datasets, often due to overfitting. Independent analyses using lesser-known datasets are crucial for a realistic assessment. My Evaluation Dataset I created a dataset of 200 sentences categorized under 50 topics, designed to challenge classification tasks. The dataset is manually labeled in English. For this evaluation, I used only the English version to avoid potential biases from using the same language model for dataset creation and topic prediction. You can check out the dataset here. Performance Results I evaluated the following models: The task was to match each sentence with the correct topic, calculating an accuracy score and error rate for each model. A lower error rate indicates better performance. Conclusion This analysis using a uniquely crafted English dataset reveals insights into the state-of-the-art capabilities of these advanced language models. GPT-4o stands out with the lowest error rate, affirming OpenAI’s performance claims. Independent evaluations with diverse datasets are essential for a clearer picture of a model’s practical effectiveness beyond standardized benchmarks. Note that the dataset is fairly small, and results may vary with different datasets. This evaluation was conducted using the English dataset only; a multilingual comparison will be conducted at a later time. 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 Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Five9 Salesforce AI Integration

Five9 Salesforce AI Integration

Five9 and Salesforce Enhance AI-Powered Solutions for Superior Customer Experiences Five9 (NASDAQ: FIVN), a provider of the Intelligent CX Platform, today announced the next step in its collaboration with Salesforce. Five9 Salesforce AI Integration. This partnership aims to deliver AI-powered solutions to enhance customer experiences (CX) in contact centers. The latest release, Five9 for Service Cloud Voice with Partner Telephony, integrates Salesforce Einstein with Five9’s suite of AI solutions. This empowers agents to better service customer requests, improves management’s understanding of contact center operations, and delivers customer resolutions that exceed expectations. Using Five9’s open APIs and Five9 TranscriptStream, the Einstein AI engine identifies opportunities to provide real-time solutions for agents, prompting ‘Next Best Action’ guidance. The solution also offers real-time transcription of customer conversations, ensures call recordings’ accuracy and relevance, and integrates with Salesforce Einstein Conversation Insights to enhance conversation intelligence. “Five9 understands the power of elevating the customer experience through innovative technology and seamless integrations,” said Dan Burkland, President of Five9. “Our collaboration with Salesforce pushes the boundaries of what is possible. Infusing Einstein’s AI insights into the contact center and CRM eliminates repetitive tasks while guiding agents with the next best actions to help them be more effective.” A Long-Standing Partnership The Salesforce-Five9 collaboration, now over 15 years strong, recently introduced Five9 call dispositions for agents within the Salesforce Omni-Channel widget or Voice Call page. This allows organizations to automatically update call dispositions in the Five9 call database, ensuring accurate reporting across the integration. Both companies are meeting the growing demand for AI solutions to enhance customer engagement throughout the customer journey. “Five9’s deeper integration with Salesforce Einstein offers a new level of choice for customers seeking AI capabilities that best match their contact center needs and existing technology investments,” said Sheila McGee-Smith, President & Principal Analyst at McGee-Smith Analytics. “Coupled with features like Five9 TranscriptStream, organizations can significantly reduce an agent’s workload while enhancing the customer’s overall experience. This next step in the Salesforce-Five9 relationship demonstrates each company’s commitment to their joint customer base, enabling them to leverage the latest AI innovations easily.” “Service Cloud Voice with Five9 uses AI to deliver a better customer experience,” said Ryan Nichols, Chief Product Officer of Service Cloud, Salesforce. “Our collaboration focuses on more than just a ‘single pane of glass’– we’re bringing together customer data, knowledge, and real-time conversation transcripts to help make agents more productive and delight customers.” Availability and Further Information These new enhancements to Five9 for Service Cloud Voice with Partner Telephony will be available starting June 30. For a deeper look into the Five9 integration with Service Cloud Voice and to explore common use cases, register for the webinar “Unlock Efficiency with the Power of AI: Five9 and Salesforce Service Cloud Voice” on Tuesday, July 23. An on-demand playback of the December 2023 Five9 and Salesforce joint webinar is also available, covering topics such as using data for personalization, best practices for leveraging engagement data to improve experiences, and how companies can become more customer-centric. Salesforce, Einstein, and other related marks are trademarks of Salesforce, Inc. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

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