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Bipartisan BIOSECURE Act
17Sep

Bipartisan BIOSECURE Act

The U.S. House of Representatives has passed the bipartisan BIOSECURE Act, targeting Chinese biotech firms such as WuXi AppTec and WuXi Biologics as national security risks. The legislation restricts American companies from partnering with these firms, potentially disrupting the drug supply chain. Bipartisan SupportThe bill passed with a strong majority of 306-81, garnering support from 111 Democrats. Representative James Comer (R-Ky.) highlighted the bill’s goal to “protect U.S. taxpayer dollars from flowing to biotechnology companies that are owned, operated, or controlled by China or other foreign adversaries.” He emphasized the importance of safeguarding sensitive healthcare data from foreign influence before these companies become more entrenched in the U.S. economy. National Security ConcernsRep. Comer and other supporters, including Representatives John Moolenaar (R-Mich.) and Raja Krishnamoorthi (D-Ill.), underscored the bill’s significance for national security and the integrity of the U.S. healthcare system. Senate ProspectsThe Bipartisan BIOSECURE Act now moves to the Senate, where it is anticipated to receive robust bipartisan support. A similar measure previously passed the Senate Committee on Homeland Security and Governmental Affairs with overwhelming approval, suggesting a favorable outcome in the full Senate. Key ProvisionsIntroduced in January 2024, the Act prohibits U.S. biopharma companies from working with certain Chinese contractors. Currently, five companies, including WuXi AppTec and WuXi Biologics, are blacklisted. An amendment allows existing contracts to remain in effect until January 1, 2032, offering some flexibility for ongoing projects. Industry ImpactAnalysts caution that the Act could disrupt the U.S. drug supply and impede clinical trials, adding strain to an already pressured supply chain. Jaxon Tan and Ivy Yang, in a BioSpace opinion piece, warned that these restrictions might significantly affect industry progress and innovation. Domestic Manufacturing ChallengesThe Act also highlights vulnerabilities in U.S. manufacturing capabilities. Fernando Muzzio, a Rutgers University professor, pointed out that the U.S. has become overly dependent on foreign manufacturing, particularly from China and India, neglecting the development of domestic production capacities. This dependence underscores the need to bolster homegrown manufacturing infrastructure. Preparing for ChangeAs the BIOSECURE Act advances, healthcare technology companies will need to prepare for potential operational changes and supply chain disruptions. Firms may need to seek alternative partnerships and invest in domestic resources to navigate these challenges effectively. While the Bipartisan BIOSECURE Act aims to enhance national security, it also presents both challenges and opportunities for the healthcare industry. Companies will need to adapt to these changes to maintain stability and continue advancing medical innovation. 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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September 17, 2024in Salesforce
GPT-o1 GPT5 Review
15Sep

GPT-o1 GPT5 Review

OpenAI has released its latest model, GPT-5, also known as Project Strawberry or GPT-o1, positioning it as a significant advancement in AI with PhD-level reasoning capabilities. This new series, OpenAI-o1, is designed to enhance problem-solving in fields such as science, coding, and mathematics, and the initial results indicate that it lives up to the anticipation. Key Features of OpenAI-o1 Enhanced Reasoning Capabilities Safety and Alignment Targeted Applications Model Variants Access and Availability The o1 models are available to ChatGPT Plus and Team users, with broader access expected soon for ChatGPT Enterprise users. Developers can access the models through the API, although certain features like function calling are still in development. Free access to o1-mini is expected to be provided in the near future. Reinforcement Learning at the Core The o1 models utilize reinforcement learning to improve their reasoning abilities. This approach focuses on training the models to think more effectively, improving their performance with additional time spent on tasks. OpenAI continues to explore how to scale this approach, though details remain limited. Major Milestones The o1 model has achieved impressive results in several competitive benchmarks: Chain of Thought Reasoning OpenAI’s o1 models employ the “Chain of Thought” prompt engineering technique, which allows the model to think through problems step by step. This method helps the model approach complex problems in a structured way, similar to human reasoning. Key aspects include: While the o1 models show immense promise, there are still some limitations, which have been covered in detail elsewhere. However, based on early tests, the model is performing impressively, and users are hopeful that these capabilities are as robust as advertised, rather than overhyped like previous projects such as SORA or SearchGPT by OpenAI. 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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September 15, 2024in Enterprise
New Slack Innovations
13Sep

New Slack Innovations

Salesforce Unveils Innovative Slack Updates Ahead of its Dreamforce conference in San Francisco later this week, Salesforce has introduced several groundbreaking updates to Slack, designed to consolidate company knowledge, data, agents, apps, and automation into a unified, agent-powered work operating system. New Slack Innovations. The latest enhancements to Slack include: Denise Dresser, CEO of Slack, commented on the updates: “Slack’s agent-powered work operating system is transforming productivity by seamlessly integrating purpose-built AI, customer data, and automation into the everyday workflow. This innovation isn’t just about improving how work gets done—it’s about unlocking new levels of productivity to drive business success across every team and department. In a complex work environment, true productivity demands a future-ready work operating system, and Slack is leading the way.” For more information on these updates and how they can benefit your organization, stay tuned for further details from Dreamforce. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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September 13, 2024in Data
IntraEdge Higher Education
13Sep

IntraEdge Higher Education

PHOENIX–(BUSINESS WIRE)–IntraEdge, Inc., a leading global technology products and services provider, recently announced its expanded investment in itsHigher Education division with the addition of new leadership to bolster their Salesforce service offerings. The new leaders each possess over 20 years of higher education experience and have a proven track record of building innovative and high performing consulting practices. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” The Higher Education division leadership team consists of Vince Salvato, Todd Edge, and Ryan Clemens. Salvato, who will be leading the division, is a recognized pioneer in Salesforce implementations for higher education. He brings a wealth of experience from his years working with higher education leaders, Salesforce, and ISV Partners. Edge and Clemens have a long history implementing Salesforce and other technologies for higher education leveraging global capabilities to assemble well balanced implementation teams. Together, this team boasts a proven track record of serving over 150 higher education institutions. Their collective history of successful Salesforce and technology implementations within higher education, coupled with IntraEdge’s 3,000+ global resources and complimentary product and service offerings, positions IntraEdge to deliver exceptional solutions. “We are thrilled to welcome Vince, Ryan, and Todd to the IntraEdge team,” said Kal Somani, CEO of IntraEdge. “Their combined experience and knowledge of the higher education landscape make them invaluable assets as we expand our footprint in this industry. By leveraging Salesforce’s powerful platform with IntraEdge’s full breadth of technology capabilities, we are confident in our ability to deliver exceptional solutions that address the unique challenges and opportunities facing higher education institutions.” IntraEdge redefines the typical implementation approach by delivering accelerated, cost-effective, and highly successful implementations. The company’s proven methodology and global delivery capabilities, combined with a team of seasoned higher education experts, will enable institutions to maximize the value of Salesforce while minimizing disruption to campus operations. IntraEdge’s Higher Education division offers a comprehensive suite of Salesforce-based solutions tailored to the specific needs of colleges and universities. With implementation, consulting, and value-add products and services, institutions can maximize the value of their Salesforce investment, including but not limited to Data Integration and Visualization, Digital Experience Strategy, Digital Content Strategy and Development, Managed and Capacity Services, AI Governance and Compliance Software. “We are excited to join IntraEdge and be a part of a world-class higher education practice,” said Salvato, Senior Vice President of Higher Education at IntraEdge. “Our team has a proven track record of success in helping higher education institutions achieve their goals. We look forward to partnering with colleges and universities to leverage the power of Salesforce to improve student outcomes and operational efficiency.” IntraEdge is proud to be a trusted partner to higher education institutions across North America. Our company is committed to delivering exceptional results and exceeding client expectations. 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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September 13, 2024in Salesforce
E-Commerce Platform Improvement
13Sep

E-Commerce Platform Improvement

Section I: Problem Statement CVS Health is continuously exploring ways to improve its e-commerce platform, cvs.com. One potential enhancement is the implementation of a complementary product bundle recommendation feature on its product description pages (PDPs). For instance, when a customer browses for a toothbrush, they could also see recommendations for related products like toothpaste, dental floss, mouthwash, or teeth whitening kits. A basic version of this is already available on the site through the “Frequently Bought Together” (FBT) section. Traditionally, techniques such as association rule mining or market basket analysis have been used to identify frequently purchased products. While effective, CVS aims to go further by leveraging advanced recommendation system techniques, including Graph Neural Networks (GNN) and generative AI, to create more meaningful and synergistic product bundles. This exploration focuses on expanding the existing FBT feature into FBT Bundles. Unlike the regular FBT, FBT Bundles would offer smaller, highly complementary recommendations (a bundle includes the source product plus two other items). This system would algorithmically create high-quality bundles, such as: This strategy has the potential to enhance both sales and customer satisfaction, fostering greater loyalty. While CVS does not yet have the FBT Bundles feature in production, it is developing a Minimum Viable Product (MVP) to explore this concept. Section II: High-Level Approach The core of this solution is a Graph Neural Network (GNN) architecture. Based on the work of Yan et al. (2022), CVS adapted this GNN framework to its specific needs, incorporating several modifications. The implementation consists of three main components: Section III: In-Depth Methodology Part 1: Product Embeddings Module A: Discovering Product Segment Complementarity Relations Using GPT-4 Embedding plays a critical role in this approach, converting text (like product names) into numerical vectors to help machine learning models understand relationships. CVS uses a GNN to generate embeddings for each product, ensuring that relevant and complementary products are grouped closely in the embedding space. To train this GNN, a product-relation graph is needed. While some methods rely on user interaction data, CVS found that transaction data alone was not sufficient, as customers often purchase unrelated products in the same session. For example: Instead, CVS utilized GPT-4 to identify complementary products at a higher level in the product hierarchy, specifically at the segment level. With approximately 600 distinct product segments, GPT-4 was used to identify the top 10 most complementary segments, streamlining the process. Module B: Evaluating GPT-4 Output To ensure accuracy, CVS implemented a rigorous evaluation process: These results confirmed strong performance in identifying complementary relationships. Module C: Learning Product Embeddings With complementary relationships identified at the segment level, a product-relation graph was built at the SKU level. The GNN was trained to prioritize pairs of products with high co-purchase counts, sales volume, and low price, producing an embedding space where relevant products are closer together. This allowed for initial, non-personalized product recommendations. Part 2: User Embeddings To personalize recommendations, CVS developed user embeddings. The process involves: This framework is currently based on recent purchases, but future enhancements will include demographic and other factors. Part 3: Re-Ranking Scheme To personalize recommendations, CVS introduced a re-ranking step: Section IV: Evaluation of Recommender Output Given that CVS trained the model using unlabeled data, traditional metrics like accuracy were not feasible. Instead, GPT-4 was used to evaluate recommendation bundles, scoring them on: The results showed that the model effectively generated high-quality, complementary product bundles. Section V: Use Cases Section VI: Future Work Future plans include: 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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September 13, 2024in Generative AI
Introhive Relationship Intelligence Platform
12Sep

Introhive Relationship Intelligence Platform

FREDERICTON, New Brunswick, September 12, 2024 – Introhive, the leading Relationship Intelligence platform, today announced that it is enabling its market leading, AI-Powered Relationship Intelligence for Salesforce Data Cloud empowering clients to understand in real-time the Relationship Intelligence associated with sales Opportunities Bringing Salesforce Data Cloud and AI together for enhanced insights Introhive’s integration brings the Customer 360 vision to life by providing a unified and enriched view of contact and relationship data, enabling organizations to derive advanced insights by overlaying their existing sales opportunities. As a leader in relationship intelligence and CRM data automation, Introhive provides unmatched data accuracy, ensuring reliable insights and actions from Data Cloud applications and AI tools like Salesforce Einstein Copilot. By transforming relationship data into actionable insights, organizations are empowered to make critical business decisions with confidence and turn connections into tangible business value. Enhanced decision-making with Salesforce Data Cloud “Our Relationship Intelligence capability for Salesforce Data Cloud enhances the solution we offer our clients and elevates Introhive’s role as a top-tier Data Ecosystem Partner on the Salesforce platform,” said Lee Blakemore, CEO of Introhive. “Clients will now enjoy all the benefits of Introhive’s Data Share, enhanced by Salesforce’s powerful platform, ensuring real-time access to trusted relationship data. This combination empowers firms to make critical business decisions with confidence and precision.” Lightning Web Components boost Salesforce Data Cloud integration To further strengthen its Salesforce offering, Introhive announced the launch of Lightning Web Components that seamlessly integrate powerful relationship intelligence in users flow of work. This strategic addition elevates relationship intelligence in Salesforce by making insights more contextual, accessible, and actionable. The components dynamically surface relevant relationship data, top contacts, and interaction history directly within Salesforce pages. This allows users to take proactive steps in managing their relationships, resulting in improved productivity, enhanced client retention, and accelerated revenue growth – all without disrupting existing workflows. Addressing data challenges with Salesforce Data Cloud integration In today’s data-driven business environment, organizations rely heavily on analytics for decision-making, recognizing that the quality and timeliness of information are crucial for effective data-driven strategies. Yet, siloed data, information overload, and constant context switching often lead to missed critical relationship insights, impeding businesses from fully leveraging their relationship capital to drive growth, retention, and informed business decisions.  Unlocking the full potential of relationship data with Salesforce Data Cloud The addition of Introhive’s lightning web components and Data Cloud integration address these challenges by transforming how businesses manage and activate their relationship data to fuel business insights and inform decision making. This includes identifying open opportunities based on relationship strength and leveraging the best connected individuals to target accounts for strategic decision making and warm introductions. “With our integration with Salesforce Data Cloud, we’re tackling a major challenge businesses face: fully unlocking the value of their relationship data,” said Leyla Samiee, Chief Product Officer at Introhive. “Our goal is to eliminate data silos that hinder organizations from obtaining crucial relationship insights. By consistently delivering clean, reliable data, we’ve been leading this charge. This new partnership takes our efforts further by enabling smooth integration of data and interactions across various systems that impact our clients’ goals. Our Lightning Web Components, now enhanced with machine intelligence, provide real-time, actionable insights more efficiently. Through our collaboration with Salesforce Data Cloud, these services are integrated with Salesforce’s interactive platforms, offering improved visibility into relationship strength and key connections. This empowers organizations to strategically engage with their most valuable accounts, fostering growth and maximizing their relationship capital.” Salesforce Data Cloud empowers growth across industries As Salesforce maintains its position as the global CRM leader, Introhive’s enhanced offering strategically empowers organizations across industries such as accounting, consulting, legal and commercial real estate, to fully capitalize on their collective relationship network to drive their business forward. For more information about Introhive’s Data Cloud integration and Lightning Web Components, visit our website. About Introhive Introhive is the leading Relationship Intelligence Platform that empowers professional services firms to dismantle silos, fuel their CRM, and activate relationship data to foster collaboration and increase revenue. Trusted by world-renowned brands, Introhive supports over 750,000 users in 90+ countries. With offices in the US, Canada, and the UK, we’re committed to helping businesses optimize their revenue opportunities. Learn more at www.introhive.com. 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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September 12, 2024in Salesforce
Salesforce Foundations
11Sep

Salesforce Foundations

Salesforce has introduced Salesforce Foundations ahead of Dreamforce, offering a significant free upgrade that enables customers to unify data and functionality from various Salesforce products into a customizable portal. This portal gives users the flexibility to apply extensive data filters and perform actions directly within the Salesforce Platform. What is Salesforce Foundations? Salesforce Foundations provides a new portal where users can access and filter data stored in Salesforce Data Cloud. This massive amount of data, coming from different Salesforce products like Sales Cloud and Service Cloud, can be easily filtered, allowing users to quickly take actions like handling support tickets or initiating upsells. The portal is fully customizable, enabling businesses to tailor the experience to their specific needs. Seamless Partner Integrations Salesforce Foundations also supports integrations with 25 partners, including well-known names like DocuSign, RingCentral, and ZoomInfo. For example, users can send and sign contracts directly from the portal using DocuSign, streamlining business processes even further. Years in the Making: Salesforce Data Cloud Evolution Salesforce has been transforming the data structures behind its applications, with many now built on the robust foundation of Salesforce Data Cloud. This cloud provides not just the data, but also the metadata, or context, which makes it easier to connect and understand relationships across different software solutions. Salesforce products and third-party solutions that integrate with the Data Cloud can now be accessed and controlled through Salesforce Foundations, allowing users to filter, display, and even act on the data from a centralized portal. Streamlining Operations with One Portal The goal of Salesforce Foundations is to streamline operations by reducing the need for multiple applications and systems. Many organizations currently juggle separate environments for Sales, Service, Marketing, and Commerce, making integrations complex. Foundations brings these applications together, enabling employees to work from a single portal, reducing screen switching, and enhancing data correlations across platforms. This promises to drive better insights and faster decision-making. AI and the Future of Salesforce Foundations Salesforce aims to make Foundations even more effective by incorporating AI to identify data correlations and suggest actions. While the extent of its capabilities will become clearer after Dreamforce, Salesforce Foundations has the potential to integrate seamlessly with the Salesforce Platform, offering all native platform features and significantly improving efficiency across organizations. 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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September 11, 2024in Salesforce Data Cloud
AI-Driven Chatbots in Education
11Sep

AI-Driven Chatbots in Education

As AI-driven chatbots enter college courses, the potential to offer students 24/7 support is game-changing. However, there’s a critical caveat: when we customize chatbots by uploading documents, we don’t just add knowledge — we introduce biases. The documents we choose influence chatbot responses, subtly shaping how students interact with course material and, ultimately, how they think. So, how can we ensure that AI chatbots promote critical thinking rather than merely serving to reinforce our own viewpoints? How Course Chatbots Differ from Administrative Chatbots Chatbot teaching assistants have been around for some time in education, but low-cost access to large language models (LLMs) and accessible tools now make it easy for instructors to create customized course chatbots. Unlike chatbots used in administrative settings that rely on a defined “ground truth” (e.g., policy), educational chatbots often cover nuanced and debated topics. While instructors typically bring specific theories or perspectives to the table, a chatbot trained with tailored content can either reinforce a single view or introduce a range of academic perspectives. With tools like ChatGPT, Claude, Gemini, or Copilot, instructors can upload specific documents to fine-tune chatbot responses. This customization allows a chatbot to provide nuanced responses, often aligned with course-specific materials. But, unlike administrative chatbots that reference well-defined facts, course chatbots require ethical responsibility due to the subjective nature of academic content. Curating Content for Classroom Chatbots Having a 24/7 teaching assistant can be a powerful resource, and today’s tools make it easy to upload course documents and adapt LLMs to specific curricula. Options like OpenAI’s GPT Assistant, IBL’s AI Mentor, and Druid’s Conversational AI allow instructors to shape the knowledge base of course-specific chatbots. However, curating documents goes beyond technical ease — the content chosen affects not only what students learn but also how they think. The documents you select will significantly shape, though not dictate, chatbot responses. Combined with the LLM’s base model, chatbot instructions, and the conversation context, the curated content influences chatbot output — for better or worse — depending on your instructional goals. Curating for Critical Thinking vs. Reinforcing Bias A key educational principle is teaching students “how to think, not what to think.” However, some educators may, even inadvertently, lean toward dictating specific viewpoints when curating content. It’s critical to recognize the potential for biases that could influence students’ engagement with the material. Here are some common biases to be mindful of when curating chatbot content: While this list isn’t exhaustive, it highlights the complexities of curating content for educational chatbots. It’s important to recognize that adding data shifts — not erases — inherent biases in the LLM’s responses. Few academic disciplines offer a single, undisputed “truth.” AI-Driven Chatbots in Education. Tips for Ethical and Thoughtful Chatbot Curation Here are some practical tips to help you create an ethically balanced course chatbot: This approach helps prevent a chatbot from merely reflecting a single perspective, instead guiding students toward a broader understanding of the material. Ethical Obligations As educators, our ethical obligations extend to ensuring transparency about curated materials and explaining our selection choices. If some documents represent what you consider “ground truth” (e.g., on climate change), it’s still crucial to include alternative views and equip students to evaluate the chatbot’s outputs critically. Equity Customizing chatbots for educational use is powerful but requires deliberate consideration of potential biases. By curating diverse perspectives, being transparent in choices, and refining chatbot content, instructors can foster critical thinking and more meaningful student engagement. AI-Driven Chatbots in Education AI-powered chatbots are interactive tools that can help educational institutions streamline communication and improve the learning experience. They can be used for a variety of purposes, including: Some examples of AI chatbots in education include: While AI chatbots can be a strategic move for educational institutions, it’s important to balance innovation with the privacy and security of student data.  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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September 11, 2024in Artificial Intelligence, Data, Einstein 1 Platform, Generative AI, Salesforce Education Cloud, Salesforce Education Solutions
Salesforce Industries AI
10Sep

Salesforce Industries AI

Salesforce has introduced Industries AI, a suite of foundational, pre-built, and customizable AI capabilities designed to address specific industry needs and challenges. This innovation aims to help customers quickly realize value by automating tasks such as matching patients to clinical trials, providing proactive maintenance alerts for vehicles and machinery, streamlining inventory management, and enhancing services for citizens and program beneficiaries. Industries AI is integrated into all 15 of Salesforce’s industry clouds, offering ready-to-use solutions for a range of sector-specific tasks. To assist customers in getting started, Salesforce has launched the AI Use Case Library, which features over 100 Industries AI capabilities. This library includes dedicated resources and use case guides for each industry cloud. The library will be regularly updated with new capabilities, such as Complaint Summaries, Patient Services & Benefits Verification, and Vehicle Telemetry Summary. Industries AI also lays the groundwork for industry-specific Agentforce agents, which will transform workflows across various roles and scales. These agents, available soon in every industry cloud, can be set up in minutes to autonomously handle business tasks, drawing on CRM data, external data, and metadata. They adhere to privacy and security guidelines and can seamlessly transfer complex cases to human agents with relevant context. As organizations increasingly recognize the urgency of adopting AI—up 700% in the last six months—Industries AI addresses the challenge of building and training AI models, which can be costly and time-consuming. By offering AI capabilities tailored to specific industry needs, Salesforce provides a cost-effective solution that delivers immediate value. Industries AI combines the robustness of an enterprise-grade platform with Salesforce’s deep industry expertise. Built on the Salesforce platform, supported by Data Cloud and the Einstein Trust Layer, it ensures safety and security. Customers can leverage pre-built prompts and industry-specific data models to achieve relevant and contextual insights. Here are some of the new capabilities announced: Jeff Amann, EVP & GM of Salesforce Industries, emphasized the mission to provide practical AI solutions across all industries, enabling organizations to harness AI’s potential efficiently. Most of these features will be generally available between October 2024 and February 2025, with ongoing updates through Salesforce’s three annual releases. Generally Available Today: Available in October 2024: Available in Beta in October 2024: Generally Available in February 2025: 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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September 10, 2024in Generative AI, Life Sciences Cloud, Public Sector Solutions
AI-Powered Field Service
09Sep

AI-Powered Field Service

Salesforce has introduced new AI-powered field service capabilities designed to streamline operations for dispatchers, technicians, and field service leaders. Leveraging the Salesforce platform and Data Cloud, these innovations aim to expedite time-consuming processes and enhance customer satisfaction by making field service operations more proactive and efficient. Why it matters: Field service teams currently spend only 32% of their time interacting with customers, with the remaining 68% consumed by administrative tasks like manually entering case notes. With 78% of field service workers in AI-enabled organizations reporting that AI helps save time, Salesforce’s new tools address these inefficiencies head-on. Key AI-driven innovations for Field Service: Availability: Paul Whitelam, GM & SVP of Salesforce Field Service, notes, “The future of field service lies in the seamless integration of AI, data, and human expertise. Our new capabilities set new standards for efficiency and service delivery.” Rudi Khoury, Chief Digital Officer at Fisher & Paykel, adds, “With Salesforce Field Service, we’re not just embracing AI and data-driven insights — we’re advancing into the future of field service, achieving unprecedented efficiency and exceptional service.” Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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September 9, 2024in Einstein Insights, Salesforce Development Services, Salesforce Manufacturing Automotive Energy, Salesforce Service Cloud
Adopting Salesforce Security Policies
07Sep

Adopting Salesforce Security Policies

Data breaches reached an all-time high in 2023, affecting more than 234 million individuals, and there’s no sign of the trend slowing down. At the center of this challenge is how organizations allocate resources to safeguard customer data. One of the most critical systems for managing this data is CRM platforms like Salesforce, used by over 150,000 U.S. businesses. However, security blind spots within Salesforce continue to pose significant risks. To address these concerns, the National Institute of Standards and Technology (NIST) offers a strategic framework for Salesforce security teams. In February 2024, NIST released Version 2.0 of its Cybersecurity Framework (CSF), marking the first major update in a decade. Key improvements include the introduction of a new “Govern” function, streamlining of categories to simplify usability, and updates to the “Respond” function to enhance incident management. This framework now applies across all industries, not just critical infrastructure. For Salesforce security leaders, these changes will significantly affect how they manage security, from aligning Salesforce practices with enterprise risk strategies to strengthening oversight of third-party apps. Here’s how these updates will influence Salesforce security going forward. What is the NIST Cybersecurity Framework 2.0? The NIST Cybersecurity Framework, first launched in 2014, was developed after an executive order by President Obama, aiming to provide a standardized set of guidelines to improve cybersecurity across critical infrastructure. The framework’s objectives include: The newly updated NIST CSF 2.0, released in 2024, expands on the original framework, providing organizations with structured, yet flexible, guidance for managing cybersecurity risks. It revolves around three core components: the CSF Core, CSF Profiles, and CSF Tiers. Key Components of NIST Cybersecurity Framework 2.0 These components help organizations understand, assess, and improve their cybersecurity posture, forming the basis for risk-informed strategies that align with organizational needs and the evolving threat landscape. Key Updates in the NIST Cybersecurity Framework 2.0 and Their Impact on Salesforce Security The 2024 updates to NIST CSF offer insights that Salesforce security leaders can use to align their strategies with evolving cybersecurity risks. Implementation Strategies for Salesforce Security Leaders To incorporate CSF 2.0 into Salesforce security operations, leaders should: Conclusion: Embracing NIST CSF 2.0 to Strengthen Salesforce Security The 2024 NIST Cybersecurity Framework updates offer crucial insights for Salesforce security leaders. By adopting these practices, organizations can enhance data protection, strengthen incident response capabilities, and ensure business continuity—critical for those relying on Salesforce for managing sensitive customer data. 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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September 7, 2024in Data, Enterprise, Salesforce, Salesforce Shield, Technology
EU AI Act
07Sep

EU AI Act

The EU AI Act is a complex piece of legislation, packed with various sections, definitions, and guidelines, making it challenging for organizations to navigate. However, understanding the EU AI Act is crucial for companies aiming to innovate with AI while staying compliant with both legal and ethical standards. Arnoud Engelfriet, chief knowledge officer at ICTRecht, an Amsterdam-based legal services firm, specializes in IT, privacy, security, and data law. As the head of ICTRecht Academy, he is responsible for educating others on AI legislation, including the AI Act. In his book AI and Algorithms: Mastering Legal and Ethical Compliance, published by Technics, Engelfriet explores the intersection of AI legislation and ethical AI development, using the AI Act as a key example. He emphasizes that while new AI guidelines can raise concerns about creativity and compliance, it’s quite necessary for organizations to grasp the current and future legal landscape to build trustworthy AI systems. Balancing Compliance and Innovation As of August 2024, the much-anticipated AI Act is in effect, with implementation timelines extending from six months to over a year. Many businesses worry that the regulations might slow down AI innovation, especially given the rapid pace of technological advancements. Engelfriet acknowledges this tension, noting that “compliance and innovation have always been somewhat at odds.” However, he believes the act’s flexible, tiered approach offers space for businesses to adapt. For instance, the inclusion of regulatory sandboxes allows companies to test AI systems safely, without releasing them into the market. Engelfriet suggests that while innovation might slow down, the safety and trustworthiness of AI systems will improve. Ensuring Trustworthy AI The AI Act aims to promote “trustworthy AI,” a term that became central to discussions after its inclusion in the first draft of the act in 2019. Although the concept remains somewhat undefined, the act outlines three key characteristics of trustworthy AI: legality, technical robustness, and ethical soundness. Engelfriet underscores that trust in AI systems is ultimately about trusting the humans behind them. “You cannot really trust a machine,” he explained, “but you can trust its designers and operators.” The AI Act requires transparency around how AI systems function, ensuring they reliably perform their intended tasks, such as making automated decisions or serving as chatbots. Ethics has gained even more prominence with the rise of generative AI. Engelfriet highlights the fragmented nature of AI ethics guidelines, which address everything from data protection to bias prevention. The EU’s Assessment List for Trustworthy AI provides a framework to guide organizations in applying ethical standards, though Engelfriet notes that it may need to be tailored to specific industry needs. The Role of AI Compliance Officers Given the complexity of AI regulations, organizations may find it overwhelming to manage compliance efforts. To meet this growing need, Engelfriet recommends appointing AI compliance officers to help companies integrate AI responsibly into their operations. ICTRecht has also developed a course, based on AI and Algorithms, to teach employees how to navigate AI compliance. Participants from various roles—particularly those in data, privacy, and risk functions—attend the course to expand their knowledge in this increasingly important area. Salesforce is developing Trailblazer content to address these challenges as well. As with GDPR, Engelfriet believes the AI Act will set the tone for future AI regulations. He advises businesses to proactively engage with the AI Act to ensure they are prepared for the evolving regulatory landscape. To get assistance exploring your EU risks, contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more 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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September 7, 2024in Generative AI
Strong AI Scalability
06Sep

Strong AI Scalability

The rapid pace of digital transformation has made scalability essential for any business looking to remain competitive. The stakes are high—without the ability to scale, businesses risk falling behind as customer demands and market conditions shift. So, what does it take to build a scalable business that can grow without compromising performance or customer satisfaction? In this Tectonic insight, we’ll cover key steps to future-proof your operations, avoid common pitfalls, and ensure your business doesn’t just keep pace with the market, but leads it. Master Scalability with Scale Center Scalability doesn’t have to be overwhelming. Salesforce’s Scale Center, available on Trailhead, provides a comprehensive learning path to help you optimize your scalability strategy. Why Scalability Is a Must-Have Scalability is critical to long-term success. As your business grows, so will the demands on your applications, infrastructure, and resources. If your systems aren’t prepared, you risk performance issues, outages, lost revenue, and dissatisfied customers. Unexpected spikes in demand—from increased customer activity or internal changes like onboarding large numbers of employees—can push systems to their limits, leading to overloads or downtime. A strong scalability plan helps prevent these issues. Here are three best practices to help scale your operations smoothly and sustainably. 1. Prioritize Proactive Scale Testing Scale testing should be a key part of your application lifecycle. Many businesses wait until performance issues arise before addressing them, which can result in maintenance headaches, poor user experiences, and challenges in supporting growth. Proactive steps to take: 2. Use the Right Tools for Seamless Scalability Choosing the right technology is crucial when scaling your business. Equip your team with tools that support growth management, and follow these tips for success: By integrating the right tools and technologies, you’ll not only stay ahead of the curve but also build a culture ready to scale. 3. Focus on Sustainable Growth Strategies Scaling requires a long-term approach. From development to deployment, a strategy that emphasizes scalability from the outset can help you avoid costly fixes down the road. Key practices include: DevOps Done Right Building secure, scalable AI applications and agents requires bridging the gap between tools and skills. Focus on crafting a thoughtful DevOps strategy that supports scalability. Scalability: A Marathon, Not a Sprint Scaling effectively is an ongoing process. Customer needs and market conditions will continue to change, so your strategies should evolve as well. Scalability is about more than just handling increased demand—it’s about ensuring stability and performance across the board. Consider these steps to enhance your approach: Committing to Scalability Scalability isn’t a one-time achievement—it’s a continuous commitment to growing smarter and stronger across all areas of your business. By embedding best practices into your day-to-day operations, you’ll ensure that your systems meet demand and prepare your business for future breakthroughs. As you develop your scalability strategy, remember that customer experience and trust should always guide your decisions. Tackling scalability proactively ensures your business can thrive no matter how market conditions change. It’s more than just a bonus feature—it’s a critical element of a smoother user experience, reduced costs, and the flexibility to pivot when necessary. By embracing these strategies, you’ll not only avoid potential challenges but also build lasting trust with your customers. In a world where loyalty is earned through exceptional experiences, a strong scalability plan is your key to long-term success. 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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September 6, 2024in Data, Hyperforce, Salesforce, Technology
Exploring Large Action Models
05Sep

Exploring Large Action Models

Exploring Large Action Models (LAMs) for Automated Workflow Processes While large language models (LLMs) are effective in generating text and media, Large Action Models (LAMs) push beyond simple generation—they perform complex tasks autonomously. Imagine an AI that not only generates content but also takes direct actions in workflows, such as managing customer relationship management (CRM) tasks, sending emails, or making real-time decisions. LAMs are engineered to execute tasks across various environments by seamlessly integrating with tools, data, and systems. They adapt to user commands, making them ideal for applications in industries like marketing, customer service, and beyond. Key Capabilities of LAMs A standout feature of LAMs is their ability to perform function-calling tasks, such as selecting the appropriate APIs to meet user requirements. Salesforce’s xLAM models are designed to optimize these tasks, achieving high performance with lower resource demands—ideal for both mobile applications and high-performance environments. The fc series models are specifically tuned for function-calling, enabling fast, precise, and structured responses by selecting the best APIs based on input queries. Practical Examples Using Salesforce LAMs In this article, we’ll explore: Implementation: Setting Up the Model and API Start by installing the necessary libraries: pythonCopy code! pip install transformers==4.41.0 datasets==2.19.1 tokenizers==0.19.1 flask==2.2.5 Next, load the xLAM model and tokenizer: pythonCopy codeimport json import torch from transformers import AutoModelForCausalLM, AutoTokenizer model_name = “Salesforce/xLAM-7b-fc-r” model = AutoModelForCausalLM.from_pretrained(model_name, device_map=”auto”, torch_dtype=”auto”, trust_remote_code=True) tokenizer = AutoTokenizer.from_pretrained(model_name) Now, define instructions and available functions. Task Instructions: The model will use function calls where applicable, based on user questions and available tools. Format Example: jsonCopy code{ “tool_calls”: [ {“name”: “func_name1”, “arguments”: {“argument1”: “value1”, “argument2”: “value2”}} ] } Define available APIs: pythonCopy codeget_weather_api = { “name”: “get_weather”, “description”: “Retrieve weather details”, “parameters”: {“location”: “string”, “unit”: “string”} } search_api = { “name”: “search”, “description”: “Search for online information”, “parameters”: {“query”: “string”} } Creating Flask APIs for Business Logic We can use Flask to create APIs to replicate business processes. pythonCopy codefrom flask import Flask, request, jsonify app = Flask(__name__) @app.route(“/customer”, methods=[‘GET’]) def get_customer(): customer_id = request.args.get(‘customer_id’) # Return dummy customer data return jsonify({“customer_id”: customer_id, “status”: “active”}) @app.route(“/send_email”, methods=[‘GET’]) def send_email(): email = request.args.get(’email’) # Return dummy response for email send status return jsonify({“status”: “sent”}) Testing the LAM Model and Flask APIs Define queries to test LAM’s function-calling capabilities: pythonCopy codequery = “What’s the weather like in New York in fahrenheit?” print(custom_func_def(query)) # Expected: {“tool_calls”: [{“name”: “get_weather”, “arguments”: {“location”: “New York”, “unit”: “fahrenheit”}}]} Function-Calling Models in Action Using base_call_api, LAMs can determine the correct API to call and manage workflow processes autonomously. pythonCopy codedef base_call_api(query): “””Calls APIs based on LAM recommendations.””” base_url = “http://localhost:5000/” json_response = json.loads(custom_func_def(query)) api_url = json_response[“tool_calls”][0][“name”] params = json_response[“tool_calls”][0][“arguments”] response = requests.get(base_url + api_url, params=params) return response.json() With LAMs, businesses can automate and streamline tasks in complex workflows, maximizing efficiency and empowering teams to focus on strategic initiatives. 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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September 5, 2024in Data, Salesforce, Technology, Third Party Apps
Machine Learning on Kubernetes
05Sep

Machine Learning on Kubernetes

How and Why to Run Machine Learning Workloads on Kubernetes Running machine learning (ML) model development and deployment on Kubernetes has become essential for optimizing resources and managing costs. As AI and ML tools gain mainstream acceptance, business and IT professionals are increasingly familiar with these technologies. With the growing buzz around AI, engineering needs in ML and AI have expanded, particularly in managing the complexities and costs associated with these workloads. The Need for Kubernetes in ML As ML use cases become more complex, training models has become increasingly resource-intensive and costly. This has driven up demand and costs for GPUs, a key resource for ML tasks. Containerizing ML workloads offers a solution to these challenges by improving scalability, automation, and infrastructure efficiency. Kubernetes, a leading tool for container orchestration, is particularly effective for managing ML processes. By decoupling workloads into manageable containers, Kubernetes helps streamline ML operations and reduce costs. Understanding Kubernetes The evolution of engineering priorities has consistently focused on minimizing application footprints. From mainframes to modern servers and virtualization, the trend has been towards reducing operational overhead. Containers emerged as a solution to this trend, offering a way to isolate application stacks while maintaining performance. Initially, containers used Linux cgroups and namespaces, but their popularity surged with Docker. However, Docker containers had limitations in scaling and automatic recovery. Kubernetes was developed to address these issues. As an open-source orchestration platform, Kubernetes manages containerized workloads by ensuring containers are always running and properly scaled. Containers run inside resources called pods, which include everything needed to run the application. Kubernetes has also expanded its capabilities to orchestrate other resources like virtual machines. Running ML Workloads on Kubernetes ML systems demand significant computing power, including CPU, memory, and GPU resources. Traditionally, this required multiple servers, which was inefficient and costly. Kubernetes addresses this challenge by orchestrating containers and decoupling workloads, allowing multiple pods to run models simultaneously and share resources like CPU, memory, and GPU power. Using Kubernetes for ML can enhance practices such as: Challenges of ML on Kubernetes Despite its advantages, running ML workloads on Kubernetes comes with challenges: Key Tools for ML on Kubernetes Kubernetes requires specific tools to manage ML workloads effectively. These tools integrate with Kubernetes to address the unique needs of ML tasks: TensorFlow is another option, but it lacks the dedicated integration and optimization of Kubernetes-specific tools like Kubeflow. For those new to running ML workloads on Kubernetes, Kubeflow is often the best starting point. It is the most advanced and mature tool in terms of capabilities, ease of use, community support, and functionality. 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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September 5, 2024in Salesforce

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