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07May

Salesforce Unified Knowledge

Salesforce Inc. is introducing a novel feature within its Data Cloud data lake, addressing the growing need for organizations to develop their own artificial intelligence models. This new feature, termed Unified Knowledge, integrates data from various third-party sources into the Data Cloud, facilitating the collection and curation of data crucial for training AI models, particularly for customer service agents. Unified Knowledge enables the importation of unstructured data into the Data Cloud, where it undergoes transformation, tagging, and quality assurance processes. This feature, developed in collaboration with Zoomin, primarily targets the enhancement of Salesforce’s Einstein for Service customer support application. However, its data integration capabilities extend to other Salesforce applications like Sales Cloud, Health Cloud, Financial Services Cloud, and Field Service. The administrative setup process for Unified Knowledge is described as relatively straightforward. Within Salesforce’s knowledge management tool, tagging tools are available, and once content is integrated into the system, much of the content can be automatically processed. Data from external sources such as Microsoft’s SharePoint, Atlassian’s Confluence, Google Drive and YouTube, Amazon Web Services’ S3 storage, Adobe’s Experience Platform, Guru Technologies’ Guru, Zendesk’s customer service platform, and company websites can be utilized to train customer-facing answer bots, streamline employee access to internal information, and facilitate quick searches within company knowledge bases. Unified Knowledge is available in a free beta test for Salesforce customers with Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. A freemium version of Unified Knowledge will continue to be included with those applications, with Salesforce Lightning Knowledge being a requirement and Classic Knowledge not being supported. In essence, Unified Knowledge aims to consolidate organizational knowledge from disparate third-party systems into Salesforce, thereby improving service agent efficiency, resolving customer cases faster, and enhancing the quality and accuracy of generative AI content. By Tectonic Salesforce Marketing Architect, Shannan Hearne. 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

May 7, 2024in Generative AI, Salesforce, Salesforce Data Cloud, Salesforce Experience Cloud, Salesforce Optimization

06May

Salesforce Unified Knowledge

Salesforce Introduces Unified Knowledge: Empowering Service Excellence with Integrated Organizational Insights Salesforce has unveiled Unified Knowledge, a groundbreaking solution designed to integrate organizational knowledge from diverse third-party systems directly into Salesforce. This innovation aims to enhance the efficiency of service agents, enabling them to resolve customer cases more swiftly and effectively. Unified Knowledge, coupled with customer data from Salesforce Data Cloud, leverages this aggregated knowledge to generate precise and personalized AI-driven content. This capability ensures faster and more tailored customer experiences. Why It Matters In today’s service landscape, 79% of organizations are investing in AI to bolster their support capabilities. However, 76% of executives face challenges in scaling AI effectively due to fragmented systems and isolated data sources. Enhancing Service with AI: Einstein for Service Built on the Einstein Trust Layer, Einstein for Service harnesses AI to elevate service team productivity and enhance customer experiences. Historically, this capability has relied on structured and unstructured customer data within Data Cloud. Unified Knowledge: Integrating Comprehensive Data Sources Unified Knowledge enriches AI models by incorporating Salesforce knowledge articles and information from external platforms such as SharePoint, Confluence, Google Drive, and corporate websites. This holistic data foundation empowers Einstein for Service with robust generative AI capabilities, ensuring agents and AI assistants deliver timely and accurate solutions. Strategic Partnership with Zoomin Powered by a strategic collaboration with Zoomin, Unified Knowledge amplifies service capabilities through: Expansion Across Salesforce Ecosystem Unified Knowledge extends beyond Service Cloud to integrate seamlessly with Salesforce Field Service, Sales Cloud, Health Cloud, and Financial Services Cloud, ensuring comprehensive data utilization across various operational domains. Salesforce Perspective “In service, enhanced knowledge and context lead to superior outcomes for both agents and customers. Unified Knowledge complements Data Cloud’s customer insights by integrating external organizational data, facilitating widespread adoption of generative AI and enabling faster, more meaningful customer engagements.” – Kishan Chetan, EVP and GM, Service Cloud Customer Reaction “Unified Knowledge enables us to deliver proactive, predictive, and preventive service to our customers. By unifying our extensive resources through a single system, our agents can swiftly provide solutions, ensuring consistent service delivery and boosting organizational productivity.” – Dharam Rai, VP, Global Customer Success & Experience, Sonos Availability Unified Knowledge is available in open beta today for Salesforce customers using Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. Knowledge Answers in Bots will be generally available in June 2024, while Einstein Copilot for Mobile Workers and Search Answers are available now. This strategic initiative underscores Salesforce’s commitment to enhancing service excellence through integrated, AI-driven solutions that empower organizations to deliver exceptional customer experiences. 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

May 6, 2024in Generative AI, Salesforce Data Cloud, Unified Knowledge

06May

Generative AI Self-Service and Unified Knowledge

Salesforce Announces Unified Knowledge to Boost Service Efficiency and Customer Experience Salesforce has introduced Unified Knowledge, a groundbreaking solution designed to integrate organizational knowledge from various third-party systems into Salesforce. This integration aims to enhance service agents’ efficiency and expedite customer case resolutions. By leveraging customer data in Salesforce Data Cloud, Unified Knowledge helps generate accurate and relevant AI-driven content, enabling faster and more personalized customer experiences. Generative AI Self-Service and Unified Knowledge. Key Importance Detailed Insights Built on the Einstein Trust Layer, Einstein for Service uses AI to boost service team productivity and customer experience. Traditionally, these AI capabilities have relied on unstructured and structured customer data within Data Cloud. Unified Knowledge enhances these AI models by incorporating Salesforce knowledge articles and resources from third-party platforms such as SharePoint, Confluence, Google Drive, and company websites. This robust data foundation empowers Einstein for Service and its generative AI capabilities to deliver precise answers to agents and AI assistants in real time. Generative AI Self-Service and Unified Knowledge Unified Knowledge, developed through a strategic partnership with Zoomin, offers several key capabilities: In addition to Service Cloud, Unified Knowledge integrates information into Salesforce Field Service, Sales Cloud, Health Cloud, and Financial Services Cloud. Salesforce’s Perspective Kishan Chetan, EVP and GM of Service Cloud, stated, “In service, more knowledge and more context translates to better answers for agents and customers. Agents and self-serve customers already benefit from a complete customer profile with information in Data Cloud. Now, with Unified Knowledge, they also have access to all external organizational data, creating a truly comprehensive foundation to fuel both the successful adoption of generative AI and the delivery of faster, more meaningful customer experiences.” Customer Reaction Dharam Rai, VP of Global Customer Success & Experience at Sonos, commented, “Unified Knowledge is helping us deliver proactive, predictive, and preventative service to our customers. We have over 500 agents educating our customers on different aspects of our products. Now, all our resources and data points can be unified through the same system quickly, enabling our agents to provide solutions faster. Every agent can deliver consistent and repeatable service to improve customer engagement and increase organizational productivity.” Availability Unified Knowledge is available today in open beta for Salesforce customers with Service Cloud Unlimited Edition, Einstein 1 Service Edition, or the Knowledge Add-On. Knowledge Answers in Bots will be generally available in June 2024, while Einstein Copilot for Mobile Workers and Search Answers are available now. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

May 6, 2024in Einstein 1 Platform, Generative AI, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Unified Knowledge

04May

Unified Knowledge for Service Agents

Salesforce has introduced a new intelligence source for service agents called Unified Knowledge. This solution aggregates information from third-party sources and integrates it into Salesforce, enhancing the customer data available in Data Cloud. Unified Knowledge Overview Enhanced Service with Unified Knowledge Unified Knowledge aggregates data from sources like SharePoint, Confluence, Google Drive, and brand websites, making it accessible within Salesforce Service Cloud. While Service Cloud has primarily utilized data from Data Cloud via Einstein for Service to assist service agents, Unified Knowledge expands this by including additional third-party information. Broader Integration Across Salesforce Although Service Cloud is a primary focus, Unified Knowledge will also integrate with Salesforce Field Service, Sales Cloud, Health Cloud, and Financial Services Cloud. This solution was developed in partnership with Zoomin Software. Technical Approach and Future Plans The initial version of Unified Knowledge does not utilize Data Cloud. Instead, it stores third-party knowledge in the KnowledgeArticle object on Core and uses Zoomin for integration. Salesforce plans to eventually transition this solution to Data Cloud for both storage and integration. This transition involves multiple dependencies and significant refactoring of the Knowledge product. For now, the current approach allows for quicker market entry. Once moved to Data Cloud, customers will need Data Cloud credits to use Unified Knowledge. Response by email from Salesforce: “The beta version of Unified Knowledge does not leverage Data Cloud. The third-party Knowledge is stored on Core in the KnowledgeArticle object, and Salesforce uses ZoomIn to integrate with third-party systems. Salesforce’s long-term vision is to move to Data Cloud — initially for the storage of third-party knowledge, and eventually for the connector/integration piece as well. This involves multiple dependencies on Data Cloud however and significant refactoring of the Knowledge product, so in order to get this solution to market more quickly, this initial version is built on Core. Once we move Unified Knowledge to Data Cloud, customers will have to purchase Data Cloud credits to use the product.” Benefits and Features of Unified Knowledge Unified Knowledge enhances the information available to service agents, potentially leading to better service experiences. Its generative AI capabilities include: By expanding the data available to service agents, Unified Knowledge aims to improve service quality 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 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

May 4, 2024in Generative AI, Salesforce Service Cloud, Unified Knowledge

29Apr

Train On Your Own Data

General-purpose large language models (LLMs) offer businesses the convenience of immediate use without requiring any special setup or customization. However, to maximize the potential of LLMs in business environments, organizations can achieve significant benefits by customizing these models through training on their own data. Custom LLMs excel at handling organization-specific tasks that generic LLMs—such as OpenAI’s ChatGPT or Google’s Gemini—may not manage as effectively. By training an LLM on data unique to the enterprise, businesses can fine-tune the model to produce responses that are highly relevant to specific products, workflows, and customer interactions. To determine whether to customize an LLM with organization-specific data, businesses should first explore the various types of LLMs and understand the advantages of fine-tuning a model on custom data sets. Following this, they can proceed with the necessary steps: identifying data sources, cleaning and formatting the data, adjusting model parameters, retraining the model, and testing it in production. Generic vs. Customized LLMs LLMs can be broadly categorized into two types: Training an LLM on custom data doesn’t imply starting from scratch; instead, it often involves fine-tuning a pre-trained generic model with additional training on the organization’s data. This approach allows the model to retain the broad knowledge it acquired during initial training while enhancing its capabilities in areas specific to the business. Benefits of Customizing an LLM The primary reason for retraining or fine-tuning an LLM is to achieve superior performance on business-specific tasks compared to using a generic model. For example, a company that wants to deploy a chatbot for customer support needs an LLM that understands its products in detail. Even if a generic LLM has some familiarity with the product from public data sources, it may lack the depth of knowledge that the company’s internal documentation provides. Without this comprehensive context, a generic LLM might struggle to generate accurate responses when interacting with customers about specific products. Generic models are optimized for broad usability, which means they may not be tailored for the specialized conversations required in business scenarios. Organizations can overcome these limitations by retraining or fine-tuning an LLM with data related to their products and services. During this process, AI teams can also adjust parameters, such as model weights, to influence the type of output the model generates, making it more relevant to the organization’s needs. Steps to Customize an LLM with Organization-Specific Data To customize an LLM with your organization’s data, follow these steps: By following these steps, organizations can transform a generic LLM into a powerful, customized tool tailored to their unique business needs, enhancing efficiency, customer satisfaction, and overall operational effectiveness. 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

April 29, 2024in Salesforce

25Apr

Salesforce Experience Cloud Summer 24 Release Notes

Customization is key, and Experience Cloud is here to help you deliver. Salesforce Experience Cloud Summer 24 Release Notes. Integrate enhanced LWR sites with Data Cloud to gain deeper insights into site visitor interactions. Elevate your site with new styling features for forms and buttons, streamlined search options, and increased control over the layout and spacing of your LWR sites. Improve your visitor login experience with a new integration framework for headless login and guest user identity flows. Stay productive on the go with a collection of updates to the Mobile Publisher app. Salesforce Experience Cloud Summer 24 Release Notes 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

April 25, 2024in Salesforce, Salesforce Experience Cloud

18Apr

Who Calls AI Ethical

Background – Who Calls AI Ethical On March 13, 2024, the European Union (EU) enacted the EU AI Act, a move that some argue has hindered its position in the global AI race. This legislation aims to ‘unify’ the development and implementation of AI within the EU, but it is seen as more restrictive than progressive. Rather than fostering innovation, the act focuses on governance, which may not be sufficient for maintaining a competitive edge. The EU AI Act embodies the EU’s stance on Ethical AI, a concept that has been met with skepticism. Critics argue that Ethical AI is often misinterpreted and, at worst, a monetizable construct. In contrast, Responsible AI, which emphasizes ensuring products perform as intended without causing harm, is seen as a more practical approach. This involves methodologies such as red-teaming and penetration testing to stress-test products. This critique of Ethical AI forms the basis of this insight,and Eric Sandosham article here. The EU AI Act To understand the implications of the EU AI Act, it is essential to summarize its key components and address the broader issues with the concept of Ethical AI. The EU defines AI as “a machine-based system designed to operate with varying levels of autonomy and that may exhibit adaptiveness after deployment. It infers from the input it receives to generate outputs such as predictions, content, recommendations, or decisions that can influence physical or virtual environments.” Based on this definition, the EU AI Act can be summarized into several key points: Fear of AI The EU AI Act appears to be driven by concerns about AI being weaponized or becoming uncontrollable. Questions arise about whether the act aims to prevent job disruptions or protect against potential risks. However, AI is essentially automating and enhancing tasks that humans already perform, such as social scoring, predictive policing, and background checks. AI’s implementation is more consistent, reliable, and faster than human efforts. Existing regulations already cover vehicular safety, healthcare safety, and infrastructure safety, raising the question of why AI-specific regulations are necessary. AI solutions automate decision-making, but the parameters and outcomes are still human-designed. The fear of AI becoming uncontrollable lacks evidence, and the path to artificial general intelligence (AGI) remains distant. Ethical AI as a Red Herring In AI research and development, the terms Ethical AI and Responsible AI are often used interchangeably, but they are distinct. Ethics involve systematized rules of right and wrong, often with legal implications. Morality is informed by cultural and religious beliefs, while responsibility is about accountability and obligation. These constructs are continuously evolving, and so must the ethics and rights related to technology and AI. Promoting AI development and broad adoption can naturally improve governance through market forces, transparency, and competition. Profit-driven organizations are incentivized to enhance AI’s positive utility. The focus should be on defining responsible use of AI, especially for non-profit and government agencies. Towards Responsible AI Responsible AI emphasizes accountability and obligation. It involves defining safeguards against misuse rather than prohibiting use cases out of fear. This aligns with responsible product development, where existing legal frameworks ensure products work as intended and minimize misuse risks. AI can improve processes such as recruitment by reducing errors compared to human solutions. AI’s role is to make distinctions based on data attributes, striving for accuracy. The concern is erroneous discrimination, which can be mitigated through rigorous testing for bias as part of product quality assurance. Conclusion The EU AI Act is unlikely to become a global standard. It may slow AI research, development, and implementation within the EU, hindering AI adoption in the region and causing long-term harm. Humanity has an obligation to push the boundaries of AI innovation. As a species facing eventual extinction from various potential threats, AI could represent a means of survival and advancement beyond our biological limitations. 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

April 18, 2024in Salesforce

18Apr

Salesforce Slack and AI

Salesforce, the customer relationship management software giant, has announced the availability of Slack AI to all paid Slack customers with expanded language support. Slack AI utilizes a company’s conversational data to assist end users and employees in quickly grasping processes and communications. It generates summaries and introduces new search capabilities based on the client company’s conversations. Slack, a workplace messaging and productivity app, was acquired by Salesforce for approximately $28 billion in 2021. It competes directly with Microsoft’s Teams and Google Chat. The Slack AI add-on is now available for all paid Slack plans (Pro and Business+) at $10 per user per month. It supports English, Spanish, and Japanese languages initially, with more languages coming soon. This development allows businesses of all sizes to leverage an intuitive AI experience seamlessly integrated with Slack, enhancing productivity within the platform. Previously, Slack AI was accessible only to large enterprises paying for Slack. The latest features of Slack AI include a recap feature providing daily morning digests with channel summaries, personalized search answers, and conversation summaries. According to internal analysis, customers using Slack AI in pilot programs are saving an average of 97 minutes per user each week by leveraging AI to find answers, distill knowledge, and generate ideas. One of Slack’s customers, Beyond Better Foods, a healthy dessert brand, uses Slack AI extensively for logistics planning. Their operations team benefits from enhanced search capabilities and channel recaps, saving time and improving focus. Andy Kung, Vice President of Operations at Beyond Better Foods, shared his experience: “When I need to get my CEO a fast answer at 2 pm on a Friday, I can use Slack AI’s search function. I’ve only been using Slack AI for about a month, but it’s already helped me quickly find answers countless times, and AI is saving me at least 30 minutes a day.” This announcement marks a significant step in making Slack AI accessible to a broader range of businesses, empowering them to work smarter and more efficiently within the Slack platform. 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

April 18, 2024in Salesforce, Salesforce Slack

14Apr

Paradox of Writing With AI

It seems like some people honestly believe they can spot AI-generated content immediately, but that’s not always the case. Well-written content isn’t inherently AI-generated, and if it is AI-generated, that doesn’t necessarily mean it’s well-written. The quality of writing often depends more on the writer’s skill than the tools they use. Paradox of Writing With AI is that it will make a good writer better. And it will make a bad writer worse. The real difference in human versus AI content lies in the accessibility of writing tools and the lack of proper ethical regulation for their use. This ease of access makes it simple for people to feel entitled to judge written content. True, if you publish your writing – online or elsewhere – you open it up for judgement. But imagine if UX design or data applications were graded as indiscriminately—those discussions would likely be confined to experts rather than becoming public debates on social media condemning all well-written content. Good writing requires creativity, flair, and uniqueness, among other skills, to truly impress readers. Good writing is well-organized and flows well with consistent style or voice from beginning to end. Good writing is also free from mistakes and errors in spelling, punctuation and grammar. But that alone doesn’t make it engaging or meaningful. A good writer will brainstorm for great ideas and follow them up with research. A good writer can think of fresh angles to view a topic. A good writer is sure to re-write and self-edit to make a better draft. AI has been integrated into various tools and applications long before ChatGPT was launched. Search engines use it to provide relevant results; social media algorithms keep your favorite content visible; Siri and Alexa rely on natural language processing and speech recognition; Netflix and Spotify use AI recommendation systems to cater to your tastes, and so on. AI enhances human ideas, not just in writing, but across many fields. Writing With AI is Inevitable For instance, Chinese Nobel laureate Mo Yan surprised everyone at the 65th-anniversary celebration of Shouhuo magazine by revealing he uses ChatGPT. During his speech praising fellow author Yu Hua, he mentioned that he struggled to write a commendation and asked a doctoral student to use ChatGPT for help. This revelation caused quite a stir, as it was unexpected for a Nobel Prize winner to use AI for writing. Why shouldn’t he? If AI makes a good writer better, then most of us should be employing it. Mo Yan isn’t alone. Rie Kudan, the 17th winner of Japan’s Akutagawa Prize, admitted to using ChatGPT for her novel, Tokyo-to Dojo-to. She stated that about 5% of the book consists of AI-generated sentences. Kudan, who is introverted, shared that frequent interactions with the AI tool allowed her to express personal thoughts she couldn’t comfortably discuss with others. ChatGPT’s responses often sparked dialogue in her novel, adding a unique dimension to her writing process. Grammarly, another AI tool, is why some people’s writing doesn’t reflect their irritation when discussing AI-generated content online. Grammarly has been widely used for editing and proofreading, ensuring users’ writing maintains a promotional tone and corrects errors without sounding sarcastic or bored. The Problem with Sounding Alike & The Uniqueness of a Writer’s Voice A significant issue with AI-generated content is that many written works sound similar. Writers need to develop unique voices. While Jane Austen, Mary Shelley, and the Brontë sisters are admirable, emulating their ornate language can interfere with communication’s primary purpose. Excessive fanciness can make speech overly flamboyant, akin to Oscar Wilde’s works. However asking AI to work through your content and put it in the voice of a known writer, add humor, or change the tense is time saving. The problem isn’t that AI enables people to produce well-crafted content. Many individuals have exceptional writing skills and huge vocabularies. The real issue is the uniformity in everyone’s writing, a lack of diversity that AI can perpetuate. Yet, you only have to Google any topic and you will find many blog posts and articles that share the same view, and perhaps the same voice. Some discussions about AI resemble early 2000s conspiracy theories about cell phones. While the context has changed, the tone remains similar. The Importance of Creativity in Writing & Our Language Creativity is essential in writing. Even AI relies on human creativity. Without our input, machines would repeatedly generate the same content. Machine learning in AI is about learning from people. Our role is crucial, demonstrating the value of our unique voices. Developing a unique voice takes time and effort, which is why creatives like Kelly McKernan, Nicki Minaj, Elin Hilderbrand, and Jonathan Franzen are suing AI companies for copyright infringement. These unique voices significantly impact language evolution, and it’s vital for us to continue growing creatively. Writers play a crucial role in language evolution by creating new words or phrases that captivate readers. Over time, these innovations can enrich the language. A writer’s distinctive style can set trends, leading to significant changes in language use. This power must be used wisely. Famous writers’ narrative structures and dialogue usage can inspire others. For example, Dr. Seuss coined “nerd,” J.R.R. Tolkien introduced “tween,” Milton created “pandemonium”, novelist William Gibson first used “cyberspace”, Johnathon Swift gave us “yahoo” in Gulliver’s Travels, and Charles Dickens gave us “boredom.” The core of a good piece of writing is a great idea. With a strong core idea, the writer can easily layer the content around it. Content even can build the framework from which comes a whole new word. Content includes interesting examples to which the reader can relate. That content needs to be well-organized and clear in form so that the reader can easily see the message or find the intended meaning. In addition, the writing should have style and the right voice that matches its topic and theme while also reflecting what the author believes. Writing Through the Centuries Writing has evolved over centuries, influencing language development. During

April 14, 2024in Salesforce Einstein

10Apr

AI in Slack

Introducing AI in Slack If you are unfamiliar with the Slack collaboration tool, learn more here. Incorporating Artificial Intelligence (AI) into Slack marks a significant milestone, one that is a real gamechanger. Slack’s ability to consolidate projects, data, and conversations into one platform has been a time saver for businesses, fostering collaboration and enhancing productivity. Now, with the introduction of native AI features, users can leverage their collective knowledge more efficiently than ever before. “For the past decade, Slack has transformed the way we work, facilitating seamless integration of people, apps, and systems. With Slack AI, we’re poised to elevate this transformation further. These new AI capabilities empower our customers to tap into the wealth of knowledge within Slack, enabling smarter work processes, faster decision-making, and more focus on innovation and growth.” Denise Dresser, CEO of Slack Enhancing Work Efficiency with AI The traditional approach to work often comes with productivity challenges, particularly when employees lack access to critical, time based information. Studies reveal that nearly half of digital workers struggle to find necessary information, leading to suboptimal decision-making. By integrating AI features into Slack, users can instantly access contextual information related to any project or policy within their organization’s history. This streamlines workflows and enables teams to make better-informed decisions efficiently. Slack’s Commitment to Simplified Work Processes Slack has always aimed to simplify work processes, bringing conversations, automation, and productivity tools into one unified platform. From channel-based discussions to real-time collaboration and process automation, Slack offers a comprehensive solution for teams. Moreover, Slack seamlessly integrates with popular tools like Salesforce, Workday, and Google Drive, facilitating smoother business operations and accelerating task completion. AI in Slack With Slack’s channel-based model serving as the foundation, users can create a centralized repository of information. Every message, canvas, and clip contributes to this repository, forming a searchable database of collective knowledge. Intelligent search functionality further enhances accessibility, enabling users to retrieve relevant information effortlessly. AI-powered features, such as channel recaps, thread summaries, and search answers, revolutionize how teams interact with information. Channel recaps provide key highlights from discussions, allowing users to catch up quickly and make informed decisions. Thread summaries condense lengthy conversations, facilitating faster comprehension and decision-making. Additionally, search answers offer concise responses to queries, leveraging relevant Slack messages to provide valuable insights. Embracing AI for Future Growth As businesses recognize the potential of AI to drive efficiency and productivity, Slack’s AI features offer a seamless transition. By embedding AI tools directly into the Slack workspace, users can harness the power of AI effortlessly, without the need for complex configurations or separate applications. Overall, Slack AI empowers teams to reach their full potential by leveraging corporate knowledge effectively. With AI-driven insights at their fingertips, teams can save time, make better decisions, and drive meaningful outcomes for their organizations. AI in Slack Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 10, 2024in Salesforce, Salesforce Einstein, Salesforce Implementation Services, Salesforce Slack

09Apr

What is Salesforce Einstein 1?

The bold new future of enterprise AI requires a new type of platform. What is Salesforce Einstein 1? One platform that can handle terabytes of disconnected data, gives you the freedom to choose your AI models, and connects directly into the flow of work, all while maintaining customer trust. The Einstein 1 Platform unifies your data, AI, CRM, development, and security into a single, comprehensive platform. It empowers IT, admins, and developers with an extensible AI platform, facilitating fast development of generative apps and automation. What is Salesforce Einstein 1 Einstein 1 has a mixture of artificial intelligence tools on the platform, and it kind of mirrors the way the core Salesforce platform is built, standardized and custom. We have out of the box AI features such as sales email generation in Sales Cloud, and service replies in Service Cloud. What is Einstein One? Einstein One seamlessly integrates our robust data platform with Data Cloud, offering a comprehensive AI and data-driven solution within our CRM service. As the leading comprehensive AI for CRM, Salesforce Einstein transforms the Customer Success Platform by incorporating a suite of integrated AI technologies, making it more intelligent and accessible to innovators worldwide. Introducing the Einstein One Platform The future of enterprise AI demands a groundbreaking platform capable of managing terabytes of diverse data, providing the flexibility to select AI models, and seamlessly integrating into daily workflows while maintaining customer trust. The Einstein One Platform consolidates data, AI, CRM, development, and security into a singular, comprehensive platform. It empowers IT, administrators, and developers with an extensible AI platform, facilitating rapid development of generative apps and automation. Salesforce has made significant investments in enhancing the Einstein One platform by introducing two prompt engineering features – a testing center and prompt engineering suggestions, demonstrating the company’s commitment to advancing AI capabilities. Data-driven and AI-driven customer experiences are vital in constructing Data Cloud. Salesforce’s predictive AI, Einstein, has been operational since 2016, conducting over a trillion predictions per week. The company continuously evolves its capabilities, introducing generative AI products like Einstein GPT, discussed at Dreamforce [2023]. ‘Customer 360′ now represents Salesforce customers’ ability to transform into customer-centric entities, delivering integrated and cohesive experiences across sales, marketing, service, and commerce. Leveraging Data Cloud, structured and unstructured engagement data comes alive, offering a personalized perspective of customer interactions. Einstein is accessible through various Salesforce products, including Sales Cloud, Service Cloud, Marketing Cloud, Salesforce Platform, Analytics Cloud, and Community Cloud. What is the Einstein One platform? Salesforce’s Einstein One is a transformative platform that securely integrates data, connects multiple Salesforce products, and empowers customer-centric businesses to create AI-driven apps, revolutionizing CRM interactions. What applications are connected with the Einstein One platform? Einstein Trust Layer: Ensuring the security of generative AI applications within Salesforce, this application acts as a safeguard for data, preventing unauthorized access. Data Cloud: Unifying structured and unstructured data, Data Cloud completes the customer 360 profile, integrating seamlessly with the Einstein One platform and making data actionable. Einstein Copilot: A built-in conversational assistant, Einstein Copilot enables users to ask questions in Natural Language and receive intelligent answers, actions, and more. Copilot Studio: An essential component of Einstein One, Copilot Studio manages Einstein One and Einstein Copilot, allowing businesses to control user access and use generative AI in their workspace. Prompt Builder, Skill Builder, Model Builder: Tools within Copilot Studio, these components empower businesses to create trusted AI prompts, add skills to user access, and choose AI models. What is Data Cloud for Einstein One? Data Cloud, combined with the Einstein Trust Layer, provides secure access to a unified data repository, forming a reliable resource for complete customer profiles and supporting AI assistants. Data Cloud facilitates valuable visualizations through reports, dashboards, and tools like Tableau, offering insights to enhance understanding of customers and business operations. What will Einstein One do for businesses? Einstein One aims to: Increase productivity Reduce operational costs Enhance the delivery of exceptional customer experiences The debut of Einstein One marks a significant stride for Salesforce and businesses, offering a secure path to boost productivity through AI technologies, ensuring continuous access to cutting-edge technologies for businesses. Where can generative AI impact businesses today? Generative AI has the potential to impact businesses by enhancing repetitive processes, making them faster. Exploring text-based processes, such as repetitive emails or form filling, is a great starting point for businesses looking to enhance capabilities. What can generative AI do for sales, service, field service teams? Generative AI can positively impact teams by automating processes, offering intelligent insights, and improving overall efficiency. Specific use cases for generative AI in sales, service, and field service teams can be explored through Salesforce’s 101 video series. What does Einstein One Tableau do? Einstein One Data Cloud, formerly known as Genie, serves as a metadata management tool connecting data from various sources. It makes data usable for AI and analysis, integrating with Einstein One, Tableau, and Salesforce’s CRM applications. Is Salesforce Einstein the same as Tableau? Formerly known as Einstein Analytics, Tableau CRM is Salesforce’s premium analytic platform, offering a powerful way to explore data, especially for current Salesforce users. Salesforce has renamed Einstein Analytics to Tableau CRM, reflecting its commitment to empowering users to make better decisions faster. In essence, the Einstein One platform combines Salesforce Data Cloud, Einstein Copilot, and the Einstein Trust Layer, providing a comprehensive solution for secure and connected data, facilitating generative AI on a comprehensive platform. Salesforce’s Einstein One Platform & the Data-Driven Revolution This innovation has the potential to revolutionize the way businesses interact with their customers. In this insight, we delve deeper into this transformative development, offering valuable insights, considerations for implementation, and the indispensable expertise of Tectonic as a data-oriented technology partner. Salesforce Data Cloud and Einstein AI are now seamlessly integrated into the Einstein One Platform. This integration empowers companies to effortlessly connect their diverse data sources, enabling the creation of AI-driven applications with minimal coding effort. Moreover, it forges a cohesive view of your data across

April 9, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Einstein Insights, Enterprise, Generative AI, Google, Mulesoft, Salesforce, Salesforce Data Cloud, Salesforce Einstein, Salesforce Sales Cloud, Technology

Salesforce for Travel, Transportation, and Hospitality

08Apr

Hotel Salesforce CRM for Hospitality

Salesforce offers hospitality professionals the tools to address marketing, sales, and customer support needs through the Marketing, Service, and Sales Cloud. Hotel Salesforce CRM for Hospitality. Customer Relationship Management (CRM) software tailored for hotels assists in engaging guests, managing reservations, coordinating projects, and streamlining communications. Hotel CRM software simplifies operations within the hospitality sector. Salesforce for Hospitality Customer Experience In the travel industry, particularly in hotels, customer experience reigns supreme. Hotels serve as temporary homes for guests, making their experience pivotal in determining future patronage. However, with the surge in travel and advancements in technology, the demand for personalized experiences has escalated. Meeting these expectations is essential not only for standing out in a competitive market but also for maintaining a positive online reputation. As travel becomes more accessible and prices decrease, managing a large volume of customers while delivering personalized experiences presents a significant challenge. Hotels must deepen their understanding of customers to avoid losing them amid the crowd. This is where CRM comes into play. CRMs for Hospitality CRM entails managing customer expectations, interactions, and loyalty to provide the most personalized journey possible. Modern CRM solutions, often cloud-based and mobile-compatible, leverage AI and big data to comprehend customers better and deliver proactive solutions, ensuring timely and relevant interactions. Hotel CRMs are specifically designed to address the unique needs of the hospitality industry. They assist in monitoring online reviews and social media chatter, enabling prompt responses to maintain a positive online reputation. Quick problem-solving is crucial in hotels, and CRM tools streamline issue resolution by providing relevant customer information promptly. Moreover, hotel CRMs enhance guest experiences by facilitating personalized journeys from initial contact to post-stay interactions. Mobile access is essential for guests, and many CRM platforms offer tools for building mobile apps and portals to enhance convenience. Hotel Salesforce CRM for Hospitality Ultimately, CRM systems empower hotels to manage customer loyalty effectively, offering better communication, multi-channel advertising, and useful employee tools. For hotels seeking these benefits, choosing the right CRM is crucial. Salesforce stands out as a top platform for hotel CRM, providing comprehensive solutions to meet diverse industry needs. In today’s travel and hospitality industry, efficiency and exceptional guest experiences are paramount. To achieve this, companies must focus on automating routine tasks, unifying data, and leveraging AI for insights. Exceptional experiences remain the best way to attract and retain customers, driving efficient growth even in challenging times. If your hotel or hospitality destination is looking to increase guest satisfaction, contact Tectonic about Salesforce today. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

April 8, 2024in Salesforce, Salesforce Hospitality Travel and Transportation

31Mar

Legacy Salesforce URL Redirection Retires

Legacy Salesforce URL Redirection Retires – Salesforce Announcement Security Notification At Salesforce, we understand that the confidentiality, integrity, and availability of your data is vital to your business, and we take the protection of your data very seriously. We’re writing to remind you that redirections for some of your Salesforce orgs’ URLs stop in the Winter ’25 release, starting in August 2024 for sandboxes and in September 2024 for production orgs. We highly encourage you to test for this change and update all references to your previous URLs before those redirections stop. Security Notification Why the Change? To comply with the latest browser and security standards, Salesforce recently required that customers deploy enhanced domains. This feature updated the hostname formats for the domains that serve Salesforce orgs. To reduce the impact of this change, your previous hostnames are redirected by default. However, to meet Salesforce security standards, some of the previous domains will be retired in 2024. The corresponding redirections stop in the Winter ’25 release. Why the Change? Actions Required Review the affected hostnames and how you can disable the redirections for testing. For details, see Prepare for the End of Redirections for Non-Enhanced Domains in Salesforce Help. Additional Resources Salesforce Enhanced Domains FAQSalesforce Help: Prepare for the End of Redirections for Non-Enhanced DomainsSalesforce Help: Log My Domain Hostname RedirectionsSalesforce Help: Enhanced Domains TimelineTo ask questions about enhanced domains, visit our monitored My Domain and Enhanced Domains group in the Trailblazer Community.We appreciate your trust in us as we continue to make your success and security our top priorities. Additional Resources Legacy Salesforce URL Redirection Retires Prepare for the End of Redirections for Non-Enhanced Domains After enhanced domains are deployed, your previous non-enhanced hostnames are redirected. Those redirections stop in Winter ’25, starting in August 2024 for sandboxes.. Review the affected hostnames and how you can disable the redirections to test before Salesforce disables them. REQUIRED EDITIONS Available in: both Salesforce Classic (not available in all orgs) and Lightning Experience Available in: Group, Essentials, Professional, Enterprise, Performance, Unlimited, and Developer Editions After enhanced domains are deployed, Salesforce redirects two categories of non-enhanced hostnames. To see if redirections are in place for a previous My Domain, check the Redirections section of the My Domain Setup page. NOTE My Domain URL redirections help prevent disruption, but they’re not intended as a permanent solution. Not all services work well with redirections, and a redirection adds a step to the process of loading the final web page. When you deploy enhanced domains, we highly recommend that you disable redirections during testing and update all references to your old URLs. Track the Source of Redirections You can search the metadata for your org to determine where the impacted URLs are used in Salesforce, but discovering all the other places that your URLs are used can be more complex. For example, site URLs and content URLs can be used on your website, social media pages, marketing materials, and templates such as email signatures and automated responses. To help you identify these locations outside of Salesforce, the Hostname Redirects log includes the referrer and origin sent with each request that Salesforce redirects. For more information, see Log My Domain Hostname Redirections. Notify Users During Redirections To help your users update outdated links and bookmarks, display a brief message during the redirection that provides the current URL. See Manage My Domain Redirections. Previous *.force.com Site Hostnames When you enable and deploy enhanced domains, the hostname formats change for your Experience Cloud sites and Salesforce Sites. To minimize potential disruption, the *.force.com hostnames that Salesforce hosted for your sites are redirected to your current site hostnames. Those redirections remain in place until Winter ’25 or until you disable these redirections. To disable these redirections for testing purposes, use an option in the Redirections section of the My Domain page and test. For more information, see Disable Redirections for Your Previous Force.com Site URLs. For the replacement format for each of these hostnames, see My Domain URL Format Changes When You Enable Enhanced Domains. To better understand the purpose of each hostname type and whether it applies to you, see My Domain Hostnames. Here are the *.force.com site hostnames for a production org that are temporarily redirected after you enable and deploy enhanced domains. Here are the .*force.com site hostnames for a sandbox that are temporarily redirected after you enable and deploy enhanced domains. Other Non-Enhanced My Domain Hostnames When you enable and deploy enhanced domains, your other previous non-enhanced My Domain hostnames are redirected. Those redirections remain in place until Winter ’25 or until you disable these redirections. For the type and the replacement format for each of these hostnames, see My Domain URL Format Changes When You Enable Enhanced Domains. To better understand the purpose of each hostname type and whether it applies to you, see My Domain Hostnames. NOTE If you deploy another My Domain change after you enable and deploy enhanced domains, these hostnames are no longer redirected. For more information, see Understand Redirections for Previous My Domain Hostnames. To disable the redirections of these non-enhanced My Domain hostnames for testing purposes, you can temporarily disable your previous My Domain. For more information, see Disable or Remove Your Previous My Domain. Here are the non-enhanced hostnames for a production org that are temporarily redirected after you enable and deploy enhanced domains. Here are the non-enhanced hostnames for a sandbox that are temporarily redirected after you enable and deploy enhanced domains. 1 If your installed package is unmanaged, the package name is c. Instanced URLs Without My Domain If your org was created before October 2020, you didn’t get a My Domain by default. In that case, your users accessed Salesforce with these hostnames that contained your instance name but not your My Domain name. These hostnames are redirected if the Instanced URL setting in the Redirections section on the My Domain Setup page is set to Redirect to the same page within the domain

March 31, 2024in Hyperforce, Salesforce, Salesforce Experience Cloud

30Mar

AI Then and Now

AI: Transforming User Interactions and Experiences Have you ever been greeted by a waitress who already knows your breakfast order? It’s a relief not to detail every aspect — temperature, how do you want your eggs, what kind of juice, bacon or sausage, etc. This example encapsulates the journey we’re navigating with AI today. AI Then and Now. This article isn’t about ordering breakfast; it’s about the evolution of user interactions, particularly how generative AI might evolve based on past trends in graphical user interfaces (GUIs) and emerging trends in AI interactions. We’ll explore the significance of context bundling, user curation, trust, and ecosystems as key trends in AI user experience in this Tectonic insight. From Commands to Conversations Let’s rewind to the early days of computing when users had to type precise commands in a Command-Line Interface (CLI). Imagine the challenge of remembering the exact command to open a file or copy data. This complexity meant that only a few people could use computers effectively. To reach a broader audience, a shift was necessary. You might think Apple’s creation of the mouse and drop down menues was the pinnacle of success, but truly the evolution predates Apple. Enter ELIZA in 1964, an early natural language processing program that engaged users in basic conversations through keyword recognition and scripted responses. Although groundbreaking, ELIZA’s interactions were far from flexible or scalable. Around the same time, Xerox PARC was developing the Graphical User Interface (GUI), later popularized by Apple in 1984 and Microsoft shortly thereafter. GUIs transformed computing by replacing complex commands with icons, menus, and windows navigable by a mouse. This innovation made computers accessible and intuitive for everyday tasks, laying the groundwork for technology’s universal role in our lives. Not only did it make computing accessible to the masses but it layed the foundation upon which every household would soon have one or more computers! The Evolution of AI Interfaces Just as early computing transitioned from the complexity of CLI to the simplicity of GUIs, we’re witnessing a parallel evolution in generative AI. User prompts are essentially mini-programs crafted in natural language, with the quality of outcomes depending on our prompt engineering skills. We are moving towards bundling complex inputs into simpler, more user-friendly interfaces with the complexity hidden in the background. Context Bundling Context bundling simplifies interactions by combining related information into a single command. This addresses the challenge of conveying complex instructions to achieve desired outcomes, enhancing efficiency and output quality by aligning user intent and machine understanding in one go. We’ve seen context bundling emerge across generative AI tools. For instance, sample prompts in Edge, Google Chrome’s tab manager, and trigger-words in Stable Diffusion fine-tune AI outputs. Context bundling isn’t always about conversation; it’s about achieving user goals efficiently without lengthy interactions. Context bundling is the difference in ordering the eggs versus telling the cook how to crack and prepare it. User Curation Despite advancements, there remains a spectrum of needs where users must refine outputs to achieve specific goals. This is especially true for tasks like researching, brainstorming, creating content, refining images, or editing. As context windows and multi-modal capabilities expand, guiding users through complexity becomes even more crucial. Humans constantly curate their experiences, whether by highlighting text in a book or picking out keywords in a conversation. Similarly, users interacting with ChatGPT often highlight relevant information to guide their next steps. By making it easier for users to curate and refine their outputs, AI tools can offer higher-quality results and enrich user experiences. User creation takes ordering breakfast from a manual conversational process to the click of a button on a vending-like system. Designing for Trust Trust is a significant barrier to the widespread adoption of generative AI. To build trust, we need to consider factors such as previous experiences, risk tolerance, interaction consistency, and social context. Without trust, in AI or your breakfast order, it becomes easier just to do it yourself. Trust is broken if the waitress brings you the wrong items, or if the artificial intelligence fails to meet your reasonable expectations. Context Ecosystems Generative AI has revolutionized productivity by lowering the barrier for users to start tasks, mirroring the benefits and journey of the GUI. However, modern UX has evolved beyond simple interfaces. The future of generative AI lies in creating ecosystems where AI tools collaborate with users in a seamless workflow. We see emergent examples like Edge, Chrome, and Pixel Assistant integrating AI functionality into their software. This integration goes beyond conversational windows, making AI aware of the software context and enhancing productivity. The Future of AI Interaction Generative AI will likely evolve to become a collaborator in our daily tasks. Tools like Grammarly and Github Copilot already show how AI can assist users in creating and refining content. As our comfort with AI grows, we may see generative AI managing both digital and physical aspects of our lives, augmenting reality and redefining productivity. The evolution of generative AI interactions is repeating the history of human-computer interaction. By creating better experiences that bundle context into simpler interactions, empower user curation, and augment known ecosystems, we can make generative AI more trustworthy, accessible, usable, and beneficial for everyone. 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

March 30, 2024in AI Tools, Artificial Intelligence, Data, Generative AI, Google, Salesforce, Salesforce Einstein, Technology

26Mar

Where Will AI Take Us?

Author Jeremy Wagstaff wrote a very thought provoking article on the future of AI, and how much of it we could predict based on the past. This insight expands on that article. Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn. These machines can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Many people think of artificial intelligence in the vein of how they personally use it. Some people don’t even realize when they are using it. Artificial intelligence has long been a concept in human mythology and literature. Our imaginations have been grabbed by the thought of sentient machines constructed by humans, from Talos, the enormous bronze automaton (self-operating machine) that safeguarded the island of Crete in Greek mythology, to the spacecraft-controlling HAL in 2001: A Space Odyssey. Artificial Intelligence comes in a variety of flavors, if you will. Artificial intelligence can be categorized in several ways, including by capability and functionality: You likely weren’t even aware of all of the above categorizations of artificial intelligence. Most of us still would sub set into generative ai, a subset of narrow AI, predictive ai, and reactive ai. Reflect on the AI journey through the Three C’s – Computation, Cognition, and Communication – as the guiding pillars for understanding the transformative potential of AI. Gain insights into how these concepts converge to shape the future of technology. Beyond a definition, what really is artificial intelligence, who makes it, who uses it, what does it do and how. Artificial Intelligence Companies – A Sampling AI and Its Challenges Artificial intelligence (AI) presents a novel and significant challenge to the fundamental ideas underpinning the modern state, affecting governance, social and mental health, the balance between capitalism and individual protection, and international cooperation and commerce. Addressing this amorphous technology, which lacks a clear definition yet pervades increasing facets of life, is complex and daunting. It is essential to recognize what should not be done, drawing lessons from past mistakes that may not be reversible this time. In the 1920s, the concept of a street was fluid. People viewed city streets as public spaces open to anyone not endangering or obstructing others. However, conflicts between ‘joy riders’ and ‘jay walkers’ began to emerge, with judges often siding with pedestrians in lawsuits. Motorist associations and the car industry lobbied to prioritize vehicles, leading to the construction of vehicle-only thoroughfares. The dominance of cars prevailed for a century, but recent efforts have sought to reverse this trend with ‘complete streets,’ bicycle and pedestrian infrastructure, and traffic calming measures. Technology, such as electric micro-mobility and improved VR/AR for street design, plays a role in this transformation. The guy digging out a road bed for chariots and Roman armies likely considered none of this. Addressing new technology is not easy to do, and it’s taken changes to our planet’s climate, a pandemic, and the deaths of tens of millions of people in traffic accidents (3.6 million in the U.S. since 1899). If we had better understood the implications of the first automobile technology, perhaps we could have made better decisions. Similarly, society should avoid repeating past mistakes with AI. The market has driven AI’s development, often prioritizing those who stand to profit over consumers. You know, capitalism. The rapid adoption and expansion of AI, driven by commercial and nationalist competition, have created significant distortions. Companies like Nvidia have soared in value due to AI chip sales, and governments are heavily investing in AI technology to gain competitive advantages. Listening to AI experts highlights the enormity of the commitment being made and reveals that these experts, despite their knowledge, may not be the best sources for AI guidance. The size and impact of AI are already redirecting massive resources and creating new challenges. For example, AI’s demand for energy, chips, memory, and talent is immense, and the future of AI-driven applications depends on the availability of computing resources. The rise in demand for AI has already led to significant industry changes. Data centers are transforming into ‘AI data centers,’ and the demand for specialized AI chips and memory is skyrocketing. The U.S. government is investing billions to boost its position in AI, and countries like China are rapidly advancing in AI expertise. China may be behind in physical assets, but it is moving fast on expertise, generating almost half of the world’s top AI researchers (Source: New York Times). The U.S. has just announced it will provide chip maker Intel with $20 billion in grants and loans to boost the country’s position in AI. Nvidia is now the third largest company in the world, entirely because its specialized chips account for more than 70 percent of AI chip sales. Memory-maker Micro has mostly run out of high-bandwidth memory (HBM) stocks because of the chips’ usage in AI—one customer paid $600 million up-front to lock in supply, according to a story by Stack. Back in January, the International Energy Agency forecast that data centers may more than double their electrical consumption by 2026 (Source: Sandra MacGregor, Data Center Knowledge). AI is sucking up all the payroll: Those tech workers who don’t have AI skills are finding fewer roles and lower salaries—or their jobs disappearing entirely to automation and AI (Source: Belle Lin at WSJ). Sam Altman of OpenAI sees a future where demand for AI-driven apps is limited only by the amount of computing available at a price the consumer is willing o pay. “Compute is going to be the currency of the future. I think it will be maybe the most precious commodity in the world, and I think we should be investing heavily to make a lot more compute.” Sam Altman, OpenAI CEO This AI buildup is reminiscent of past technological transformations, where powerful interests shaped outcomes, often at the expense of broader societal considerations. Consider early car manufacturers. They focused on a need for factories, components, and roads.

March 26, 2024in Generative AI

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