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2024 AI and Machine Learning Trends

2024 AI and Machine Learning Trends

In 2023, the AI landscape experienced transformative changes following the debut of ChatGPT in November 2022, a landmark event for artificial intelligence. 2024 AI and Machine Learning Trends ahead, AI is set to dramatically alter global business practices and drive significant advancements across various sectors. Organizations are shifting their focus from experimental initiatives to real-time applications, reflecting a more mature understanding of AI’s capabilities while still being intrigued by generative AI technologies. Key AI and Machine Learning Trends for 2024 Here are the top trends shaping the AI and machine learning landscape for 2024: 1. Agentic AIAgentic AI is evolving from reactive to proactive systems. Unlike traditional AI that primarily responds to user inputs, these advanced AI agents demonstrate autonomy, proactivity, and the ability to independently set and pursue goals. 2. Open-Source AIOpen-source AI is democratizing access to sophisticated AI models and tools by offering free, publicly accessible alternatives to proprietary solutions. This trend has seen significant growth, with notable competitors like Mistral AI’s Mixtral models and Meta’s Llama 2 making strides in 2023. 3. Multimodal AIMultimodal AI integrates various types of inputs—such as text, images, and audio—mimicking human sensory capabilities. Models like GPT-4 from OpenAI showcase this ability, enhancing applications in fields like healthcare by improving diagnostic precision. 4. Customized Enterprise Generative AI ModelsThere is a rising interest in bespoke generative AI models tailored to specific business needs. While broad tools like ChatGPT remain widely used, niche-specific models are increasingly popular for their efficiency in addressing specialized requirements. 5. Retrieval-Augmented Generation (RAG)RAG combines text generation with information retrieval to boost the accuracy and relevance of AI-generated content. By reducing model size and leveraging external data sources, RAG is well-suited for business applications that require up-to-date factual information. 6. Shadow AIShadow AI, which refers to user-friendly AI tools used without formal IT approval, is gaining traction among employees seeking quick solutions or exploring new technologies. While it fosters innovation, it also raises concerns about data privacy and security. Looking Ahead to 2024 These trends highlight AI and machine learning’s expanding role across industries in 2024. Organizations must adapt to these advancements to remain competitive, balancing innovation with strong governance frameworks to ensure security and compliance. Staying informed about these developments will be crucial for leveraging AI’s transformative potential in the coming year. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Cool New AI Tools

Cool New AI Tools

In the rapidly growing world of artificial intelligence, staying abreast of the latest tools is not merely advantageous but imperative. As AI technology advances, so do the instruments that revolutionize problem-solving, innovation, and business growth. Whether you are an experienced developer, an aspiring entrepreneur, or simply interested in the expansive potential of AI, this insight offers a comprehensive guide to the newest and most impactful AI tools available. Additionally, startups and developers can now register their AI projects at no cost by visiting genai.works. Let us dig into this exciting wave of innovation. AI Tools Overview AI for Content & Voiceovers Parlandi AI: Accessible at parlandi.com, this tool enables the generation of various text content such as articles, blogs, advertisements, and media in 53 languages. Additionally, users can create AI-generated images by simply describing them, leveraging solutions like OpenAI DALL-E-2, DALL-E-3, DALL-E-3 HD, and Stable Diffusion by Stability.ai. AI for Clip Generation 10LevelUp: Available at 10levelup.com, this platform automates the creation of viral clips from YouTube videos, facilitating channel growth with minimal user input by generating engaging clips within minutes. AI for In-Depth Qualitative Research ResearchGOAT: Found at researchgoat.com, ResearchGOAT harnesses the burgeoning capabilities of generative AI to design, field, and analyze custom research studies across various vertical markets, geographical regions, and consumer cohorts. AI for Customer Support ChatFly: Accessible via chatfly.co, ChatFly is a robust platform for developing AI-driven chatbots. It empowers businesses to create intelligent bots using their data, which can be seamlessly integrated into existing systems to enhance customer support. AI to Automate Document Processes Base64.ai Document AI: Available at base64.ai, this leading no-code AI solution comprehends documents, photos, and videos, facilitating the automation of document-related processes. AI for Job & CV Management Xtramile: Accessible through lnkd.in, Xtramile offers an Office Add-in that allows the dissemination of job offers across job boards with a single click, streamlining the recruitment process. Conclusion Empower your operations and innovate with these cutting-edge AI tools, tailored to meet a variety of business needs from content creation and customer support to qualitative research and job management. Embrace the future of AI and unlock new potentials for growth and efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Fine Tune Your Large Language Model

Fine Tune Your Large Language Model

Revamping Your LLM? There’s a Superior Approach to Fine Tune Your Large Language Model. The next evolution in AI fine-tuning might transcend fine-tuning altogether. Vector databases present an efficient means to access and analyze all your business data. Have you ever received redundant emails promoting a product you’ve already purchased or encountered repeated questions in different service interactions? Large language models (LLMs), like OpenAI’s ChatGPT and Google’s Bard, aim to alleviate such issues by enhancing information-sharing and personalization within your company’s operations. However, off-the-shelf LLMs, built on generic internet data, lack access to your proprietary data, limiting the nuanced customer experience. Additionally, these models might not incorporate the latest information—ChatGPT, for instance, only extends up to January 2022. To customize off-the-shelf LLMs for your company, fine-tuning requires integrating your proprietary data, but this process is costly, time-consuming, and may raise trust concerns. A superior alternative is a vector database, described as “a new kind of database for the AI era.” This database offers the benefits of fine-tuning while addressing privacy concerns, promoting data unification, and saving time and resources. Fine-tuning involves training an LLM for specific tasks, such as analyzing customer sentiment or summarizing a patient’s health history. However, it is resource-intensive and fails to resolve the fundamental issue of fragmented data across your organization. A vector database, organized around vectors that describe different types of data, can seamlessly integrate with an LLM or the prompt. By storing and organizing data with an emphasis on vectors, this database streamlines access to relevant information, eliminating the need for fine-tuning and unifying enterprise data with your CRM. This is pivotal for the accuracy, completeness, and efficiency of AI outputs. Unstructured data, comprising 90% of corporate data, poses a challenge for LLMs due to its varied formats. A vector database resolves this by allowing AI to process unstructured and structured data, delivering enhanced business value and ROI. Ultimately, a company’s proprietary data serves as the cornerstone for constructing an enterprise LLM. A vector database ensures seamless storage and processing of this data, facilitating better decision-making across all business applications. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Salesforce Chat GPT

What’s Happening with ChatGPT and Salesforce

ChatGPT and Salesforce The integration of ChatGPT with Salesforce presents an opportunity to streamline organizational processes, resulting in significant time savings. This integration not only enhances CRM data management with generative AI but also takes the customer experience to new heights. Integration Process: To integrate ChatGPT with Salesforce, the typical process involves creating an account on the OpenAI platform and generating an API key. These steps ensure successful integration by providing API access and authentication credentials. It’s crucial to treat the API key with the same security measures as a password to safeguard the integration. Salesforce and OpenAI Collaboration: While Salesforce offers access to AI through its Einstein GPT suite of products, Salesforce Admins and Developers have also begun directly integrating with OpenAI’s APIs and various AppExchange apps. They are incorporating these tools into their offerings to introduce new AI-powered features, enhancing their platforms’ capabilities. Role of ChatGPT and Salesforce Admins: ChatGPT does not aim to replace Salesforce Admins but rather to augment their effectiveness and productivity. Admins with strong analytical and administrative skills can leverage ChatGPT to expedite configuration tasks. However, mastering the collaboration with ChatGPT is essential to enhance the quality of results. Understanding ChatGPT: ChatGPT, developed by OpenAI, represents a breakthrough in AI beyond conventional chatbots. It operates on the OpenAI GPT-3.5 family of large language models, incorporating both supervised and reinforcement learning techniques. Backed by OpenAI, ChatGPT employs natural language processing (NLP) to interact conversationally, mirroring human dialogue. OpenAI, founded in San Francisco, boasts substantial support from industry leaders like Microsoft. OpenAI and GPT-4: OpenAI recently unveiled GPT-4, the latest iteration of its popular ChatGPT model. GPT-4 boasts enhanced capabilities, including image processing and increased word processing capacity. With millions of users since its launch, ChatGPT continues to evolve, offering unparalleled NLP functionality. Top Use Cases for ChatGPT in Salesforce: Explore the potential of ChatGPT and Salesforce with features and scenarios, including natural language processing, chatbots, predictive sales, personalized communication, and analysis of conversational data. Einstein GPT: Salesforce introduces Einstein GPT, the world’s first generative AI for CRM. Einstein GPT enables the generation of tailored content from CRM data, ensuring relevance in every interaction, be it emails, reports, knowledge articles, or code snippets. Community Insights: As the AI landscape, particularly ChatGPT, continues to evolve, it’s essential to understand its implications for the Salesforce ecosystem. The Salesforce community acknowledges the power of ChatGPT as a sophisticated chatbot built on advanced AI technology, poised to revolutionize various Salesforce roles and experiences. What is Salesforce doing with ChatGPT? The integration between ChatGPT and Salesforce can optimize a significant portion of organizational processes, resulting in considerable time savings. This not only enhances CRM data management, now powered by generative AI, but also elevates the customer experience to a new level. Can we integrate ChatGPT with Salesforce? This typically involves creating an account on the OpenAI platform and generating an API key. To set up your API access and authentication credentials for a successful ChatGPT for Salesforce integration, follow the steps below. Treat your API key like a password to protect the security of your integration. Is Salesforce using OpenAI? While Salesforce enables customers to access it via its Einstein GPT suite of products, Salesforce Admins and Developers have also started integrating directly with OpenAI’s APIs and the many AppExchange apps. They are now embedding it into their offerings to deliver new AI-powered features. ChatGPT has shown the world the potential of AI beyond simple chatbots. Join Tectonic on the AI journey and learn about How to use ChatGPT for Salesforce, Its use cases, Integration and how you can implement it in Salesforce. Salesforce’s new marketing message is AI + Data + CRM. It all adds up to customer magic. At the heart of this magic is Generative AI or GPT, not ChatGPT. Of course, AI advancements will mean very different things across the wide variety of Salesforce roles and day-to-day experiences. With more and more “GPT” tools being launched each week, how is the Salesforce community using the Chat variety in their day-to-day roles, and how do they see it evolving over the coming months and years? ChatGPT is nothing more than a chatbot, akin to Einstein bots. However, it’s a powerful one! Built on the OpenAI GPT-3.5 family of large language models and both supervised and reinforcement learning techniques, ChatGPT was trained on a vast amount of internet text with a cutoff in January 2022. It has been optimized for natural language processing tasks such as text generation, question answering, translation, and text classification. The technology behind ChatGPT is advanced and continues to evolve, relying on machine learning and deep learning techniques. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Is Prompt Engineering Dying?

The Rise and Fall of Prompt Engineering Prompt engineering is everywhere—it’s the hot topic in the AI world. The World Economic Forum, OpenAI’s Sam Altman, and the Twitterverse can’t stop talking about it. My feeds are filled with ads promoting courses that promise to make you a fortune with minimal effort. But here’s the uncomfortable truth: prompt engineering is already facing its decline. Don Giannatti originally wrote on this topic in June of 2023. Whic got us thinking, is prompt engineering dying? Why Is Prompt Engineering Fading? Reason 1: AI Is Getting Smarter AI is advancing rapidly. Machines are starting to understand our words and phrases just like we do, similar to a child learning to talk. The need for finely tuned prompts is decreasing because AI is developing the ability to generate its own prompts simply by interpreting questions. It’s learning all the time. Reason 2: AI Crafts Its Own Prompts SDon already usea minimal nudge prompts, which AI then expands into detailed, contextually accurate prompts. GPT-4 can do this, and GPT-5 will have it even more integrated. While prompt engineering has been trendy among marketers and tech enthusiasts, its relevance is quickly waning. Reason 3: Prompts Are Limited in Versatility Prompts are tailored for specific AI models and versions, limiting their flexibility. AI can overcome these limitations more efficiently than humans. Machine learning excels in reducing input and friction, and AI is quickly learning and improving upon human-made prompts. The Future: Problem Formulation The enduring skill in the AI age is problem formulation—how we identify, analyze, and define problems. When we can clearly illustrate a problem, AI can provide efficient solutions. AI cannot identify unquantifiable problems that aren’t part of existing systems—that’s still a human strength, for now. Prompt Engineering vs. Problem Formulation Prompt engineering focuses on the words, sentence structure, and punctuation. Problem formulation is about defining the problem—seeing the bigger picture and broader strokes. Without a well-defined problem, even the best-crafted prompt is just a set of words. Why Problem Formulation Matters Problem formulation has been overshadowed by problem-solving. It’s not easy, isn’t taught in universities, and isn’t popularized by futurists. Yet, it’s essential. Executives often struggle with diagnosing problems—85% of them say so. To stay ahead, we need better problem formulation. Four Ways to Enhance Problem Formulation Embracing AI Wisely AI is evolving quickly. To leverage its potential, we must clearly identify problems. Once defined, AI can generate prompts to find solutions. A Take on AI While one can appreciate the educational and helpful capabilities of GPT and other language models, be cautious about the rapid integration of AI into our lives without adequate discussion or input from society. I trust AI more than the billionaires driving its adoption, but be wary of their motivations. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Top Ten Reasons Why Tectonic Loves the Cloud The Cloud is Good for Everyone – Why Tectonic loves the cloud You don’t need to worry about tracking licenses. Read more

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Benioff Dreams of AI Making Messaging Intelligent

Benioff Dreams of AI Making Messaging Intelligent

During the company’s recent earnings call, Salesforce CEO Marc Benioff spoke about the “revolutionary” impacts of generative AI, emphasizing the immense potential it holds for the tech industry. Benioff Dreams of AI Making Messaging Intelligent. Benioff highlighted Salesforce’s integration of OpenAI’s ChatGPT platform into Slack, the workplace messaging app owned by Salesforce. This integration aims to enhance Slack’s capabilities by enabling features such as conversation summarization, research assistance, and message drafting directly within the platform. Benioff expressed his vision for Slack to become intelligent itself, leveraging the wealth of data stored within the platform. He emphasized the transformative potential of generative AI in providing intelligent support to users, potentially revolutionizing customer service interactions and business operations. Salesforce’s clients, including Gucci, are already leveraging AI to enhance customer service experiences, reflecting the growing adoption of AI-driven solutions across various industries. Generative AI offers benefits such as time-saving automation of routine tasks, efficient research gathering, and concise information delivery, benefiting individuals in personal, professional, and academic contexts. However, concerns regarding the ethical implications of generative AI have also surfaced, including issues related to deepfake images, bias, and potential job displacement. Some advocate for stricter regulation and careful assessment of AI’s risks before further development. Benioff Dreams of AI Making Messaging Intelligent Despite these concerns, Benioff remains optimistic about the transformative potential of generative AI, describing it as a revolution that will reshape the world in unprecedented ways. He believes that we are only at the beginning of this AI revolution, with much more innovation and transformation yet to come. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Tableau Pulse and Tableau GPT

Announcing Tableau Pulse and Tableau GPT

It’s fair to say that many are familiar with ChatGPT, the groundbreaking Large Language Model from OpenAI that has transformed how we work and interact with AI. At TC 2023, Tableau announced a new tool called Tableau GPT. But what exactly is Tableau GPT, and how does it fit into Tableau’s suite of products? Announcing Tableau Pulse and Tableau GPT. Tableau GPT Tableau GPT is an assistant leveraging the advanced capabilities of generative AI to simplify and democratize data analysis. Built from Einstein GPT, a Salesforce product developed in collaboration with OpenAI, Tableau GPT integrates generative AI into Tableau’s user experience. This integration aims to help users work smarter, learn faster, and communicate more effectively. During the Devs on Stage segment of the keynote at TC, Matthew Miller, Senior Director of Product Management, showcased Tableau GPT’s ability to generate calculations. For example, with a prompt like “Extract email addresses from JSON,” Tableau GPT quickly produces a calculation that users can copy into the calculation window. Tableau Pulse Tableau GPT also powers a new tool called Tableau Pulse, designed to generate powerful insights swiftly. Tableau Pulse provides “data digests” on a personalized metrics homepage, offering a curated, ‘newsfeed’-like experience of key KPIs. As users interact with Pulse, it learns to deliver more personalized results based on their interests. For example, Tableau Pulse highlights metrics that require attention, derived from recent data trends identified by Tableau GPT. The tool provides the latest metric values, visual trends, and AI-generated insights for user-selected KPIs. Tableau Pulse also enables users to ask questions about their data in natural language. For instance, when asked, “What is driving change in Appliance Sales?” Tableau Pulse responded with a brief answer and visualization. Further inquiries, such as “What else should I know about air fryers?” revealed that the “inventory fill rate” for air fryers is forecasted to fall below a set threshold, providing actionable insights that users can share across their organization. Future Impact and Availability Tableau GPT and Pulse promise to revolutionize interactions with Tableau products, enabling quicker visualization creation and making data accessible to non-technical users. Salesforce announced that Tableau Pulse and Tableau GPT would enter pilot testing later this year. When they do, we’ll be ready to share new insights. Follow us on LinkedIn to stay updated on all the latest developments and features in Tableau! Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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AI Drives Insights

AI Drives Insights

Innovations from Salesforce, HubSpot, and One AI are driving deeper insights and streamlining processes. Key Takeaways: AI is transforming the way businesses operate, and customer relationship management (CRM) is no exception. AI has been influencing the CRM space for years, but its impact is now reaching new heights. By harnessing AI algorithms, modern CRM systems offer predictive analytics and deeper insights, enabling brands to understand their customers on an unprecedented level. Advanced AI-enabled CRMs even incorporate sentiment analysis to gauge customer perceptions and provide automation tools to free marketers from mundane tasks. The global AI market, currently valued at $142.3 billion, continues to expand rapidly. From 2020 to 2022, annual corporate investments in AI startups increased by $5 billion, reflecting the growing demand for AI-driven innovations. As CRM vendors introduce more AI capabilities, it’s important to understand the unique approaches each one takes to differentiate themselves and deliver specific benefits. Salesforce and Einstein GPT: A New Era with OpenAI’s ChatGPT On March 7, 2023, Salesforce introduced Einstein GPT, a generative AI technology integrated into its CRM platform. Combining real-time data from Salesforce’s Data Cloud with OpenAI’s ChatGPT, Einstein GPT allows users to input natural-language prompts to streamline tasks and decision-making. Salesforce has long invested in AI. In 2017, it launched its Einstein AI as part of Service Cloud. By 2019, Salesforce had partnered with OpenAI to explore AI research and integrate advanced models into its ecosystem. The acquisition of Slack in 2020 further strengthened its AI capabilities by incorporating advanced messaging and communication tools into the CRM environment. Marc Benioff, CEO of Salesforce, highlighted the significance of AI’s growth: “The world is experiencing one of the most profound technological shifts with real-time technologies and generative AI. This comes at a pivotal moment as every company is focused on connecting with their customers in more intelligent, automated, and personalized ways.” Einstein GPT is set to transform customer engagement, with applications across Salesforce’s various platforms, including Tableau, MuleSoft, and Slack. HubSpot CRM: AI-Powered Content Assistant A day before Salesforce’s AI announcement, HubSpot revealed its own AI-powered features: the Content Assistant and ChatSpot.ai. These tools aim to enhance CRM users’ productivity while creating stronger connections with customers. HubSpot’s Content Assistant helps marketing and sales teams ideate, create, and share content through generative AI capabilities. It can suggest blog titles, create content outlines, and assist with crafting content for blogs, emails, landing pages, and websites. ChatSpot.ai, on the other hand, offers a natural-language chat experience to simplify CRM tasks for HubSpot users. HubSpot has also invested in AI for other functions, including conversation intelligence, data enrichment, predictive analytics, and content optimization, solidifying its position in the AI-driven CRM landscape. With AI advancements from companies like Salesforce, HubSpot, and One AI, the future of CRM is poised for enhanced efficiency, automation, and personalized customer interactions. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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Slack and ChatGPT

Slack and ChatGPT

Salesforce Inc announced its collaboration with OpenAI, the creator of ChatGPT, to integrate the chatbot technology into its Slack collaboration software and broaden the use of generative artificial intelligence across its business software. The San Francisco-based company unveiled EinsteinGPT, a technology merging its own AI capabilities with those of external partners like OpenAI. This collaboration aims to assist businesses in tasks such as drafting emails, managing customer accounts, and even generating computer code. Additionally, ChatGPT will integrate with Slack to help users summarize conversations and handle various queries. This strategic move reflects the competitive landscape among tech giants racing to enhance their platforms with generative AI, which can generate text, images, and other content based on historical data inputs. Microsoft Corp, for example, leveraging its investment in OpenAI, has integrated generative AI into its Teams product, enabling functionalities like generating meeting notes and suggesting email responses through its Viva Sales subscription. This places Teams in direct competition with Slack. Clara Shih, a general manager at Salesforce, highlighted during a press briefing that this announcement addresses the growing demand from businesses for advanced AI capabilities. She emphasized that Salesforce’s proprietary data and AI models would differentiate their offerings in the market. Salesforce’s initiative in generative AI is poised to transform customer engagement strategies for businesses, according to Shih, enabling them to innovate profoundly in their interactions with customers. In addition to this integration, Salesforce also unveiled a new fund aimed at investing in startups specializing in generative AI technologies. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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ChatGPT and Einstein GPT

ChatGPT and Einstein GPT

Artificial intelligence (AI) has been rapidly advancing globally, with breakthroughs captivating professionals across various sectors. One milestone that has gained significant attention is the emergence of ChatGPT, a cutting-edge language model revolutionizing the tech landscape. This development has profoundly impacted businesses relying on Salesforce for their customer relationship management (CRM) needs. In March 2023, Salesforce unveiled its latest AI innovation, Einstein GPT, promising to transform how companies engage with their clientele. In this article, we explore what Salesforce Einstein GPT entails and how it can benefit teams across diverse industries. When OpenAI introduced ChatGPT in November 2022, they didn’t expect the overwhelming response it received. Initially positioned as a “research preview,” this AI chatbot aimed to refine existing technology while soliciting feedback from users. However, ChatGPT quickly became a viral sensation, surpassing OpenAI’s expectations and prompting them to adapt to its newfound popularity. Developed on the foundation of the GPT-3.5 language model, ChatGPT was specifically tailored to facilitate engaging and accessible conversations, distinguishing it from its predecessors. Its launch attracted a diverse user base keen to explore its capabilities, prompting OpenAI to prioritize addressing potential misuse and enhancing its safety features. As ChatGPT gained traction, it caught the attention of Salesforce, a leading CRM provider. In March 2023, Salesforce unveiled Einstein GPT, its own AI innovation, poised to transform customer engagement. Built on the GPT-3 architecture and seamlessly integrated into Salesforce Clouds, Einstein GPT promised to revolutionize how businesses interact with their clientele. Einstein GPT boasts a range of features designed to personalize customer experiences and streamline workflows. From generating natural language responses to crafting personalized content and automating tasks, Einstein GPT offers versatility and value across industries. By leveraging both Einstein AI and GPT technology, businesses can unlock unprecedented efficiency and deliver superior customer experiences. Despite its success, OpenAI acknowledges the need for ongoing refinement and vigilance, emphasizing the importance of responsible deployment and transparency in the development of AI technology. Exploring Einstein GPT Salesforce presents Einstein GPT as the premier generative AI tool for CRM worldwide. Utilizing the advanced GPT-3 architecture, Einstein GPT seamlessly integrates into all Salesforce Clouds, including Tableau, MuleSoft, and Slack. This groundbreaking technology empowers users to generate natural language responses to customer inquiries, craft personalized content, and compose entire email messages on behalf of sales personnel. With its high degree of customization, Einstein GPT can be finely tuned to meet the specific needs of various industries, use cases, and customer requirements, delivering significant value to businesses of all sizes and sectors. Objectives of Salesforce AI Einstein GPT Salesforce AI Einstein GPT is designed to achieve several key objectives: Distinguishing Einstein GPT from Einstein AI Einstein GPT represents the latest evolution of Salesforce’s Einstein artificial intelligence technology. Unlike its predecessors, Einstein GPT integrates proprietary Einstein AI models with ChatGPT and other leading large language models. This integration enables users to interact with CRM data using natural language prompts, resulting in highly personalized, AI-generated content and triggering powerful automations that enhance workflows and productivity. By leveraging both Einstein AI and GPT technology, businesses can achieve unparalleled efficiency and deliver exceptional customer experiences. Features of Einstein GPT in Salesforce CRM Key features and capabilities of Salesforce Einstein chatbot GPT include: Utilizing Einstein GPT for Business Improvement Einstein GPT can be leveraged across various domains to enhance business operations: Integration with Salesforce Data Cloud Salesforce Data Cloud, a cloud-based data management system, enables real-time data aggregation from diverse sources. Einstein GPT utilizes unified customer data profiles from the Salesforce Data Cloud to personalize interactions throughout the customer journey. OpenAI on ChatGPT Methods We trained this model using Reinforcement Learning from Human Feedback (RLHF), using the same methods as InstructGPT, but with slight differences in the data collection setup. We trained an initial model using supervised fine-tuning: human AI trainers provided conversations in which they played both sides—the user and an AI assistant. We gave the trainers access to model-written suggestions to help them compose their responses. We mixed this new dialogue dataset with the InstructGPT dataset, which we transformed into a dialogue format. To create a reward model for reinforcement learning, we needed to collect comparison data, which consisted of two or more model responses ranked by quality. To collect this data, we took conversations that AI trainers had with the chatbot. We randomly selected a model-written message, sampled several alternative completions, and had AI trainers rank them. Using these reward models, we can fine-tune the model using Proximal Policy Optimization. We performed several iterations of this process. ChatGPT is fine-tuned from a model in the GPT-3.5 series, which finished training in early 2022. You can learn more about the 3.5 series here. ChatGPT and GPT-3.5 were trained on an Azure AI supercomputing infrastructure. Limitations ChatGPT and Einstein GPT Salesforce Einstein GPT signifies a significant advancement in AI technology, empowering businesses to deliver tailored customer experiences and streamline operations. With its integration into Salesforce CRM and other platforms, Einstein GPT offers unprecedented capabilities for personalized engagement and automated insights, ensuring organizations remain competitive in today’s dynamic market landscape. When OpenAI quietly launched ChatGPT in late November 2022, the San Francisco-based AI company didn’t anticipate the viral sensation it would become. Initially viewed as a “research preview,” it was meant to showcase a refined version of existing technology while gathering feedback from the public to address its flaws. However, the overwhelming success of ChatGPT caught OpenAI off guard, leading to a scramble to capitalize on its newfound popularity. ChatGPT, based on the GPT-3.5 language model, was fine-tuned to be more conversational and accessible, setting it apart from previous iterations. Its release marked a significant milestone, attracting millions of users eager to test its capabilities. OpenAI quickly realized the need to address potential misuse and improve the model’s safety features. Since its launch, ChatGPT has undergone several updates, including the implementation of adversarial training to prevent users from exploiting it (known as “jailbreaking”). This technique involves pitting multiple chatbots against each other to identify and neutralize malicious behavior. Additionally,

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