OCR - gettectonic.com - Page 2
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

Read More
September 17, 2024in Salesforce
Healthcare Cloud Computing
14Sep

Healthcare Cloud Computing

Cloud Computing in Healthcare: Ensuring HIPAA Compliance Amid Growing Adoption As healthcare organizations increasingly turn to cloud computing for scalable and accessible IT services, ensuring HIPAA compliance remains a top priority. The global healthcare cloud computing market is projected to grow from $53.8 billion in 2024 to $120.6 billion by 2029, according to a MarketsandMarkets report. A 2023 Forrester report also highlighted that healthcare organizations are spending an average of .5 million annually on cloud services, with public cloud adoption on the rise. While cloud computing offers benefits like enhanced data mobility and cost efficiency, maintaining a HIPAA-compliant relationship with cloud service providers (CSPs) requires careful attention to regulations, establishing business associate agreements (BAAs), and proactively addressing cloud security risks. Understanding HIPAA’s Role in Cloud Computing The National Institute of Standards and Technology (NIST) defines cloud computing as a model that provides on-demand access to shared computing resources. Based on this framework, the U.S. Department of Health and Human Services (HHS) Office for Civil Rights (OCR) has issued guidance on how HIPAA’s Security, Privacy, and Breach Notification Rules apply to cloud computing. Under the HIPAA Security Rule, CSPs classified as business associates must adhere to specific standards for safeguarding protected health information (PHI). This includes mitigating the risks of unauthorized access to administrative tools and implementing internal controls to restrict access to critical operations like storage and memory. HIPAA’s Privacy Rule further restricts the use or disclosure of PHI by CSPs, even in cases where they offer “no-view services.” CSPs cannot block a covered entity’s access to PHI, even in the event of a payment dispute. Additionally, the Breach Notification Rule requires business associates, including CSPs, to promptly report any breach of unsecured PHI. Healthcare organizations engaging with CSPs should consult legal counsel and follow standard procedures for establishing HIPAA-compliant vendor relationships. The Importance of Business Associate Agreements (BAAs) A BAA is essential for ensuring that a CSP is contractually bound to comply with HIPAA. OCR emphasizes that when a covered entity engages a CSP to create, receive, or transmit electronic PHI (ePHI), the CSP becomes a business associate under HIPAA. Even if the CSP cannot access encrypted PHI, it is still classified as a business associate due to its involvement in storing and processing PHI. In 2016, the absence of a BAA led to a $2.7 million settlement between Oregon Health & Science University and OCR after the university stored the PHI of over 3,000 individuals on a cloud server without the required agreement. BAAs play a crucial role in defining the permitted uses of PHI and ensure that both the healthcare organization and CSP understand their responsibilities under HIPAA. They also outline protocols for breach notifications and security measures, ensuring both parties are aligned on handling potential security incidents. Key Cloud Security Considerations Despite the protections of a BAA, there are inherent risks in partnering with any new vendor. Staying informed on cloud security threats is vital for mitigating potential risks proactively. In a 2024 report, the Cloud Security Alliance (CSA) identified misconfiguration, inadequate change control, and identity management as the top threats to cloud computing. The report also pointed to the rising sophistication of cyberattacks, supply chain risks, and the proliferation of ransomware-as-a-service as growing concerns. By understanding these risks and establishing clear security policies with CSPs, healthcare organizations can better safeguard their data. Prioritizing security, establishing robust BAAs, and ensuring HIPAA compliance will allow healthcare organizations to fully leverage the advantages of cloud computing while maintaining the privacy and security of patient information. 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

Read More
September 14, 2024in Salesforce
Challenges for Rural Healthcare Providers
12Sep

Challenges for Rural Healthcare Providers

Rural healthcare providers have long grappled with challenges due to their geographic isolation and limited financial resources. The advent of digital health transformation, however, has introduced a new set of IT-related obstacles for these providers. EHR Adoption and New IT Challenges While federal legislation has successfully promoted Electronic Health Record (EHR) adoption across both rural and urban healthcare organizations, implementing an EHR system is only one component of a comprehensive health IT strategy. Rural healthcare facilities encounter numerous IT barriers, including inadequate infrastructure, interoperability issues, constrained resources, workforce shortages, and data security concerns. Limited Broadband Access Broadband connectivity is essential for leveraging health IT effectively. However, there is a significant disparity in broadband access between rural and urban areas. According to a Federal Communications Commission (FCC) report, approximately 96% of the U.S. population had access to broadband at the FCC’s minimum speed benchmark in 2019, compared to just 73.6% of rural Americans. The lack of broadband infrastructure hampers rural organizations’ ability to utilize IT features that enhance care delivery, such as electronic health information exchange (HIE) and virtual care. Rural facilities, in particular, rely heavily on HIE and telehealth to bridge gaps in their services. For instance, HIE facilitates data sharing between smaller ambulatory centers and larger academic medical centers, while telehealth allows rural clinicians to consult with specialists in urban centers. Additionally, telehealth can help patients in rural areas avoid long travel distances for care. However, without adequate broadband access, these services remain impractical. Despite persistent disparities, the rural-urban broadband gap has narrowed in recent years. Data from the FCC indicates that since 2016, the number of people in rural areas without access to 25/3 Mbps service has decreased by more than 46%. Various programs, including the FCC’s Rural Health Care Program and USDA funding initiatives, aim to expand broadband access in rural regions. Interoperability Challenges While HIE adoption is rising nationally, rural healthcare organizations lag behind their urban counterparts in terms of interoperability capabilities, as noted in a 2023 GAO report. Data from a 2021 American Hospital Association survey revealed that rural hospitals are less likely to engage in national or regional HIE networks compared to medium and large hospitals. Rural providers often lack the economic and technological resources to participate in electronic HIE networks, leading them to rely on manual data exchange methods such as fax or mail. Additionally, rural providers are less likely to join EHR vendor networks for data exchange, partly due to the fact that they often use different systems from those in other local settings, complicating health data exchange. Federal initiatives like TEFCA aim to improve interoperability through a network of networks approach, allowing organizations to connect to multiple HIEs through a single connection. However, TEFCA’s voluntary participation model and persistent barriers such as IT staffing shortages and broadband gaps still pose challenges for rural providers. Financial Constraints Rural hospitals often operate with slim profit margins due to lower patient volumes and higher rates of uninsured or underinsured patients. The financial strain is exacerbated by declining Medicare and Medicaid reimbursements. According to KFF, the median operating margin for rural hospitals was 1.5% in 2019, compared to 5.2% for other hospitals. With limited budgets, rural healthcare organizations struggle to invest in advanced health IT systems and the necessary training and maintenance. Many small rural hospitals are turning to cloud-based EHR platforms as a cost-effective solution. Cloud-based EHRs reduce the need for substantial upfront hardware investments and offer monthly subscription fees, some as low as $100 per month. Workforce Challenges The healthcare sector is facing widespread staff shortages, including a lack of skilled health IT professionals. Rural areas are disproportionately affected by these shortages. An insufficient number of IT specialists can impede the adoption and effective use of health IT in these regions. To address workforce gaps, the ONC suggests strategies such as cross-training multiple staff members in health IT functions and offering additional training opportunities. Some networks, like OCHIN, have secured grants to develop workforce programs, but limited broadband access can hinder participation in virtual training programs, highlighting the need for expanded broadband infrastructure. Data Security Concerns Healthcare data breaches have surged, with a 256% increase in large breaches reported to the Office for Civil Rights (OCR) over the past five years. Rural healthcare organizations, often operating with constrained budgets, may lack the resources and staff to implement robust data security measures, leaving them vulnerable to cyber threats. A cyberattack on a rural healthcare organization can disrupt patient care, as patients may need to travel significant distances to reach alternative facilities. To address cybersecurity challenges, recent legislative efforts like the Rural Hospital Cybersecurity Enhancement Act aim to develop comprehensive strategies for rural hospital cybersecurity and provide educational resources for staff training. In the interim, rural healthcare organizations can use free resources such as the Health Industry Cybersecurity Practices (HICP) publication to guide their cybersecurity strategies, including recommendations for managing vulnerabilities and protecting email systems. Does your practice need help meeting these challenges? Contact Tectonic today. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

Read More
September 12, 2024in Salesforce Health and Life Sciences Solutions, Salesforce Managed Services, Salesforce Optimization
guide to RAG
30Aug

Tectonic Guide to Rag Part 2

The first notable change in the field of language models is the significant expansion of context window sizes and a reduction in token costs. For instance, Anthropic’s largest model, Claude, has a context window exceeding 200,000 tokens, while recent reports indicate that Gemini’s context window can reach up to 10 million tokens. Under such circumstances, Retrieval-Augmented Generation (RAG) may no longer be necessary for many tasks, as all required data can be accommodated within the expanded context window. Several financial and analytical projects have already demonstrated that tasks can be solved without needing a vector database as intermediate storage. This trend of reducing token costs and increasing context window sizes is likely to continue, potentially decreasing the need for external mechanisms in LLMs, although they are still relevant for the time being. If the context window remains insufficient, methods for summarization and context compression have been introduced. LangChain, for example, offers a class called ConversationSummaryMemory to address this challenge. pythonCopy codellm = OpenAI(temperature=0) conversation_with_summary = ConversationChain( llm=llm, memory=ConversationSummaryMemory(llm=OpenAI()), verbose=True ) conversation_with_summary.predict(input=”Hi, what’s up?”) Knowledge Graphs As the volume of data continues to grow, navigating through it efficiently becomes increasingly critical. In certain cases, understanding the structure and attributes of data is essential for effective use. For example, if the data source is a company’s wiki, an LLM might not recognize a phone number unless the structure or metadata indicates that it’s the company’s contact information. Humans can infer meaning from conventions, such as the subdirectory “Company Information,” but standard RAG may miss such connections. This challenge can be addressed by Knowledge Graphs, also known as Knowledge Maps, which provide both raw data and metadata that illustrates how different entities are interconnected. This method is referred to as Graph Retrieval-Augmented Generation (GraphRAG). Graphs are excellent for representing and managing structured, interconnected information. Unlike vector databases, they excel at capturing complex relationships and attributes among diverse data types. Creating a Knowledge Graph The process of creating a knowledge graph typically involves collecting and structuring data, which requires expertise in both the subject matter and graph modeling. However, LLMs can automate a significant portion of this process by analyzing textual data, identifying entities, and recognizing their relationships, which can then be represented in a graph structure. In many cases, an ensemble of vector databases and knowledge graphs can improve accuracy, as discussed previously. For example, search functionality might combine keyword search through a regular database (e.g., Elasticsearch) and graph-based queries. LangChain can also assist in extracting structured data from entities, as demonstrated in this code example: pythonCopy codedocuments = parse_and_load_data_from_wiki_including_metadata() graph_store = NebulaGraphStore( space_name=”Company Wiki”, tags=[“entity”] ) storage_context = StorageContext.from_defaults(graph_store=graph_store) index = KnowledgeGraphIndex.from_documents( documents, max_triplets_per_chunk=2, space_name=space_name, tags=[“entity”] ) query_engine = index.as_query_engine() response = query_engine.query(“Tell me more about our Company”) Here, searching is conducted based on attributes and related entities, instead of similar vectors. If set up correctly, metadata from the company’s wiki, such as its phone number, would be accessible through the graph. Access Control One challenge with this system is that data access may not be uniform. For instance, in a wiki, access could depend on roles and permissions. Similar issues exist in vector databases, leading to the need for access management mechanisms such as Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), and Relationship-Based Access Control (ReBAC). These access control methods function by evaluating paths between users and resources within graphs, such as in systems like Active Directory. To ensure the integrity of data during the ingestion phase, metadata related to permissions must be preserved in both the knowledge graph and vector database. Some commercial vector databases already have this functionality built in. Ingestion and Parsing Data needs to be ingested into both graphs and vector databases, but for graphs, formatting is especially critical since it reflects the data’s structure and serves as metadata. One particular challenge is handling complex formats like PDFs, which can contain diverse elements like tables, images, and text. Extracting structured data from such formats can be difficult, and while frameworks like LLama Parse exist, they are not always foolproof. In some cases, Optical Character Recognition (OCR) may be more effective than parsing. Enhancing Answer Quality Several new approaches are emerging to improve the quality of LLM-generated answers: While these advancements in knowledge graphs, access control, and retrieval mechanisms are promising, challenges remain, particularly around data formatting and parsing. However, these methods continue to evolve, enhancing LLM capabilities and efficiency. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more Alphabet Soup of Cloud Terminology As with any technology, the cloud brings its own alphabet soup of terms. This insight will hopefully help you navigate Read more

Read More
August 30, 2024in Data
Healthcare Cybersecurity Act
27Aug

Healthcare Cybersecurity Act

Lawmakers have introduced the Healthcare Cybersecurity Act in the House of Representatives, aiming to enhance protections for healthcare data amid a surge of cyberattacks targeting the industry. The bipartisan bill is spearheaded by Representatives Jason Crow (D-Colo.), Brian Fitzpatrick (R-Pa.), and Andy Kim (D-N.J.). A Senate companion bill was introduced in July 2024 by Senators Jacky Rosen (D-Nev.), Todd Young (R-Ind.), and Angus King (I-Me.). The legislation mandates a collaboration between the Cybersecurity and Infrastructure Security Agency (CISA) and the Department of Health and Human Services (HHS) to strengthen cybersecurity within the healthcare sector. It also seeks to make cyber defense resources available to nonfederal healthcare entities. Lawmakers cited a 2022 HHS Office for Civil Rights (OCR) report showing a 107% rise in data breaches involving unsecured protected health information since 2018. “Hospitals and health centers are critical parts of our nation’s infrastructure,” said Fitzpatrick. “With the alarming increase in cyberattacks, we must act swiftly to prevent data breaches, rising healthcare costs, and compromised patient care.” The bill calls for more coordination between CISA and HHS to manage cybersecurity risks. It proposes the appointment of a special liaison within CISA to act as a point of contact with HHS, ensuring better communication and threat sharing during cybersecurity incidents. If passed, the Healthcare Cybersecurity Act would also require HHS and CISA to submit a report detailing their efforts to improve cybersecurity coordination. Past collaborations between HHS and CISA include the October 2023 release of a healthcare cybersecurity toolkit, which provides industry-specific resources for managing and mitigating cyber threats. The toolkit combines materials like CISA’s cyber hygiene services and HHS’s Health Industry Cybersecurity Practices. “The bipartisan Healthcare Cybersecurity Act will play a vital role in protecting patient data, healthcare provider capabilities, and our broader cybersecurity infrastructure,” said King, stressing the need for decisive action in this area. 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

Read More
August 27, 2024in Salesforce Health and Life Sciences Solutions
Box Acquires Alphamoon
07Aug

Box Acquires Alphamoon

Box Inc. has acquired Alphamoon to enhance its intelligent document processing (IDP) capabilities and its enterprise knowledge management AI platform. Now that Box acquires Alphamoon, it will imr improves IDP. Box Acquires Alphamoon IDP goes beyond traditional optical character recognition (OCR) by applying AI to scanned paper documents and unstructured PDFs. While AI technologies like natural language processing (NLP), workflow automation, and document structure recognition have been around for some time, Alphamoon introduces generative AI (GenAI) into the mix, providing advanced capabilities. According to Rand Wacker, Vice President of AI Product Strategy at Box, the integration of GenAI helps not only with summarizing and extracting content from documents but also with recognizing document structures and categorizing them. GenAI works alongside existing OCR and NLP tools, making the digital conversion of paper documents more accurate. Box Acquires Alphamoon – Not LLM Although Box hasn’t acquired a large language model (LLM) outright, it has gained a toolkit that will enhance its Box AI platform. Box AI already uses retrieval-augmented generation to combine a user’s content with external LLMs, ensuring data security while training Box AI to better recognize and categorize documents. Alphamoon’s technology will further refine this process, enabling administrators to create tools more efficiently within the Box ecosystem. “For example, if Alphamoon’s OCR misreads or misextracts something, the system can adjust that specific part and feed it back into the LLM,” Wacker explained. “This approach is powered by an LLM, but it’s specifically trained to understand the documents it encounters, rather than relying on generic content from the internet.” Previewing an upcoming report from Deep Analysis, founder Alan Pelz-Sharpe shared that a survey of 500 enterprises across various industries, including financial services, manufacturing, healthcare, and government, revealed that 53% of enterprise documents still exist on paper. This highlights the need for Box users to have more precise tools to digitize contracts, letters, invoices, faxes, and other paper-based documents. Alphamoon’s generative AI-driven IDP solution allows for human oversight to ensure that attributes are correctly imported from the original documents. Pelz-Sharpe noted that IDP is challenging, but AI has made significant advancements, especially in handling imperfections like crumpled paper, coffee stains, and handwriting. He added that this acquisition addresses a critical gap for Box, which previously relied on partners for these capabilities. Box Buys Alphamoon – Integration Box plans to integrate Alphamoon’s tools into its platform later this year, with deeper integrations expected next year. These will include no-code app-building capabilities related to another acquisition, Crooze, as well as Box Relay’s forms and document generation tools. 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

Read More
August 7, 2024in Generative AI
AI-Powered Smarter Media
10Jun

AI-Powered Smarter Media

Transforming Retail Media: Personalization and Faster Monetization with Smarter Media Dentsu, a leading growth and transformation partner, has announced a strategic collaboration with Salesforce, the world’s #1 AI-powered CRM, to launch Smarter Media—an innovative solution designed to accelerate retail media monetization through personalized buying experiences powered by AI. Why Smarter Media Matters With shifting consumer priorities, personalized retail experiences are more critical than ever. Salesforce research highlights that: Smarter Media addresses this growing demand by enabling retailers to quickly adapt, offering tailored buying experiences that strengthen customer loyalty while driving revenue. What is Smarter Media? Smarter Media combines the power of Salesforce’s ecosystem—including Media Cloud, Sales Cloud, and Marketing Cloud Engagement—to deliver an end-to-end retail media solution. The platform assesses a brand’s retail media maturity, identifies gaps, and creates a roadmap to optimize media, technology, and skills. The solution simplifies access to advanced media technology, empowering brands to connect with customers 24/7, expand their customer base, and nurture long-term relationships. Key Features and Benefits 1. Comprehensive Assessment 2. AI-Powered Personalization 3. Built for Retail Media Success 4. Quick and Easy Adoption How Smarter Media Works Smarter Media combines Salesforce Sales Cloud’s leading sales and pipeline management tools with Media Cloud’s Advertising Sales Management application. The result is a solution that seamlessly supports both simple and complex retailer models: Real-World Value Across Retail By addressing challenges like fragmented media strategies and inaccessible technology, Smarter Media delivers transformative value for retailers: Driving Innovation Together Paul Lynch, Integrated Solutions Lead for Commerce and Retail at Dentsu UK&I, shared: “Smarter Media will democratize cutting-edge technology for brands by providing a one-stop solution to create personalized buying experiences. In today’s experience economy, maintaining compelling customer relationships has never been more vital.” Christopher Dean, SVP and GM for Communications, Media & Entertainment at Salesforce, added: “By combining Salesforce Media Cloud’s industry-specific solutions with Dentsu’s creative retail media expertise, we’re making advanced media technology accessible for retailers, helping them thrive in a competitive market.” The Future of Retail Media Smarter Media from Dentsu and Salesforce offers a transformative approach to retail media, empowering brands to deliver personalized experiences, improve customer loyalty, and accelerate revenue growth—all while leveraging cutting-edge AI and automation. With its ability to deliver value in just six months, Smarter Media is the ultimate solution for retailers looking to succeed in today’s fast-paced, customer-centric market. 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

Read More
June 10, 2024in Data, Salesforce, Salesforce Media Cloud, Technology
Roles in AI
21Sep

Salesforce’s Quest for AI for the Masses

The software engine, Optimus Prime (not to be confused with the Autobot leader), originated in a basement beneath a West Elm furniture store on University Avenue in Palo Alto. A group of artificial intelligence enthusiasts within Salesforce, seeking to enhance the impact of machine learning models, embarked on this mission two years ago. While shoppers checked out furniture above, they developed a system to automate the creation of machine learning models. Thus Salesforce’s Quest for AI for the Masses started. Despite being initially named after the Transformers leader, the tie-in was abandoned, and Salesforce named its AI program Einstein. This move reflects the ambitious yet practical approach Salesforce takes in the AI domain. In March, a significant portion of Einstein became available to all Salesforce users, aligning with the company’s tradition of making advanced software accessible via the cloud. Salesforce, although now an industry giant, retains its scrappy upstart identity. When the AI trend gained momentum, the company aimed to create “AI for everyone,” focusing on making machine learning affordable and accessible to businesses. This populist mission emphasizes practical applications over revolutionary or apocalyptic visions. Einstein’s first widely available tool is the Einstein Intelligence module, designed to assist salespeople in managing leads effectively. It ranks opportunities based on factors like the likelihood to close, offering a practical application of artificial intelligence. While other tech giants boast significant research muscle, Salesforce focuses on providing immediate market advantages to its customers. Einstein Intelligence The Einstein Intelligence module employs machine learning to study historical data, identifying factors that predict future outcomes and adjusting its model over time. This dynamic approach allows for subtler and more powerful answers, making use of various data sources beyond basic Salesforce columns. Salesforce’s AI team strives to democratize AI by offering ready-made tools, ensuring businesses can benefit from machine learning without the need for extensive customization by data scientists. The company’s multi-tenant approach, serving 150,000 customers, keeps each company’s data separate and secure. Salesforce’s Quest for AI for the Masses To scale AI implementation across its vast customer base, Salesforce developed Optimus Prime. This system automates the creation of machine learning models for each customer, eliminating the need for extensive manual involvement. Optimus Prime, the AI that builds AIs, streamlines the process and accelerates model creation from weeks to just a couple of hours. Salesforce plans to expand Einstein’s capabilities, allowing users to apply it to more customized data and enabling non-programmers to build custom apps. The company’s long-term vision includes exposing more of its machine learning system to external developers, competing directly with AI heavyweights like Google and Microsoft in the business market. Originally published in WIRED magazine on August 2, 2017 and rewritten for this insight. 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

Read More
September 21, 2017in Artificial Intelligence, Data, Einstein 1 Platform, Generative AI, Google, Salesforce, Salesforce Einstein
  • 1
  • 2

Subscribe to our mailing list. Join our mail list to receive our newsletter

We'll keep you up to date with our latest news, insights, free resources, and much more.
Don't worry, we won't spam you.
gettectonic.com