AI and automation are reshaping the workplace. The new features unveiled at Dreamforce 2024 highlight how Slack and Salesforce are helping organizations work smarter, not harder. With these capabilities, teams can accelerate their performance and deliver better outcomes.
By using a Knowledge Table to categorize and tag documents and then converting that information into a Knowledge Graph, enterprises can streamline the search process in RAG systems
Google Prepares AI-Powered Jarvis Agent for Automated Browser Tasks in Chrome Google is reportedly gearing up to launch “Project Jarvis,” an AI-powered browser agent designed to automate tasks directly within the Chrome ecosystem. According to The Information, the tool is expected to roll out in December to select users and will leverage Google’s advanced Gemini 2.0 AI model. Jarvis aims to simplify repetitive online tasks, such as organizing information or booking reservations, offering a seamless and efficient digital assistant embedded within Chrome. This initiative reflects Google’s broader vision to enhance user experiences by automating web-based routines, making its browser a central hub for task automation. Anthropic Expands Desktop Automation with Claude 3.5 Sonnet Anthropic, a key player in the AI landscape, has advanced its Claude 3.5 model with a new “Computer Use” feature, enabling direct interaction with a user’s desktop. This update allows Claude to perform tasks such as typing, clicking, and managing multiple applications, making it a powerful tool for automating workflows like data entry, document management, and customer service. Available through APIs and platforms like Amazon Bedrock and Google Cloud’s Vertex AI, Claude’s new capabilities position it as a versatile solution for businesses seeking desktop-level automation, contrasting Google Jarvis’s browser-specific approach. By interpreting screen elements, Claude’s “Computer Use” mode supports broader applications beyond web tasks, offering businesses an edge in efficiency and scalability. How Google Jarvis Stands Out Unlike Anthropic’s desktop-oriented Claude Sonnet, Google Jarvis focuses on automating tasks within Chrome. Jarvis analyzes screenshots of web pages, interprets user commands, and executes actions like clicks or data entry. While still in development, Jarvis’s design suggests a future where mundane web-based tasks are seamlessly handled by AI. Powered by Google’s Gemini 2.0 language model, Jarvis is tailored for users who prioritize web-specific functions, creating a user-friendly assistant that requires no external software. This aligns with Google’s strategy to deepen integration within its ecosystem, making Chrome a more intuitive and productive environment. Microsoft’s Copilot Agents Lead Business Automation Microsoft, meanwhile, continues to enhance its Copilot AI agents, particularly within Dynamics 365. These specialized agents are designed to automate industry-specific workflows, from lead qualification in sales to financial data reconciliation. Unlike Google Jarvis or Anthropic Claude, Microsoft’s Copilot agents target enterprise users, embedding automation within business applications like Teams, Outlook, and SharePoint. With tools like Copilot Studio, organizations can customize workflows to meet specific needs, offering a level of flexibility that resonates with enterprise clients. Early adopters, including Vodafone and Cognizant, have reported significant productivity gains through these integrations. Microsoft’s efforts position Copilot as a robust partner for day-to-day operations, transforming tasks like analysis, project coordination, and document management into automated, efficient processes. Competing Visions for AI Agents As Google, Anthropic, and Microsoft refine their AI strategies, they’re carving out distinct niches in the AI agent landscape: These approaches highlight the diverse applications of AI agents, from enhancing individual user experiences to transforming business operations. 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
By adopting a NaaS model, businesses can optimize their networks for the future while focusing on what matters most—their core mission. The era of “hands-free” networking has arrived, and it’s redefining the IT landscape
How Salesforce Drives Digital Transformation in Governmental Agencies in 2025 In the evolving digital age, government agencies face an increasing demand to modernize their services, improve citizen engagement, and deliver seamless digital experiences. These organizations require transformational technologies that not only streamline internal operations but also adopt a citizen-first approach. Salesforce emerges as a key enabler of this transformation, empowering government agencies with tools to build unified, transparent platforms while fostering efficiency and enhancing citizen interaction. Leveraging Salesforce Commerce Cloud and Salesforce CRM, agencies can overcome common challenges and embrace a more digitally enabled public sector. Let’s explore the pressing challenges government agencies face and how Salesforce provides practical, scalable solutions to address them. 1. Citizen Engagement and Accessibility: Bridging the Digital Divide Challenge: Citizens now expect government services to be as user-friendly and accessible as private-sector experiences. Lengthy response times, disconnected platforms, and inconsistent experiences across digital and physical touchpoints erode trust and hinder accessibility. Solution: 2. Data Security and Compliance: Safeguarding Citizen Trust Challenge: Handling sensitive citizen data requires robust security and strict compliance with regulations like GDPR, CCPA, and other local data privacy laws. Solution: 3. Legacy Systems and Integration: Modernizing Infrastructure Challenge: Legacy systems often limit agility, making it difficult to integrate new technologies and slowing the pace of digital transformation. Solution: 4. Budget Constraints: Implementing Cost-Effective Solutions Challenge: Budget limitations often hinder the adoption of new technologies, especially those requiring significant upfront investment. Solution: 5. Efficient Service Delivery: Streamlining Workflows Challenge: Paper-heavy, bureaucratic processes delay service delivery and frustrate both staff and citizens. Solution: 6. Data-Driven Decision-Making: Analytics for Informed Policies Challenge: Generating actionable insights from vast amounts of data is challenging, affecting policymaking and government efficiency. Solution: 7. Enhancing Collaboration: A Unified Workforce Challenge: Siloed departments hinder collaboration and reduce overall productivity, making it difficult to provide cohesive citizen services. Solution: 8. Real-Time Responsiveness: Meeting Citizen Expectations Challenge: Citizens expect real-time support and proactive communication from government agencies. Delays lead to frustration and diminished trust. Solution: Transforming Government Services with Salesforce Salesforce Commerce Cloud and Salesforce CRM are tailored to address public sector challenges in 2025. By leveraging these tools, government agencies can: Salesforce offers a clear path to a digitally empowered future, enabling government agencies to meet today’s demands while laying the foundation for innovation. Ready to Transform?If your agency is ready to embrace digital transformation, streamline operations, and enhance citizen services, Salesforce can help you get there. Let’s discuss how Salesforce solutions, supported by expert implementation, can drive meaningful change for your organization and your citizens. 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
Clippy-gate: Why Salesforce vs. Microsoft is More Than a Marketing Spat Salesforce and Microsoft are clashing once again, this time over AI and intelligent agents. What started as a seemingly lighthearted joke by Salesforce CEO Marc Benioff at Dreamforce—mocking Microsoft’s Copilot as a “Clippy 2.0″—has escalated into a significant dispute. This confrontation extends beyond the typical vendor rivalry, touching on enterprise AI’s future and its implications for businesses. A History of Rivalry Salesforce and Microsoft have a long history of competition. Past disputes included lawsuits and marketing stunts, such as Microsoft’s ill-fated 2010 Dreamforce gimmick involving a “defecting” Salesforce customer. While the two companies briefly found common ground under Microsoft CEO Satya Nadella, this détente dissolved amidst antitrust challenges over Microsoft’s LinkedIn acquisition and an aborted attempt to acquire Salesforce. Benioff has since reverted to openly criticizing Microsoft. The latest round of hostilities centers on Microsoft’s announcement of ten AI agents for Dynamics 365, coinciding with the release of Salesforce’s Agentforce. Benioff has doubled down, accusing Microsoft of overhyping Copilot and failing to meet enterprise AI standards. Benioff’s Allegations Benioff’s critiques have been relentless. He has accused Microsoft of misleading customers about AI capabilities, claiming that Copilot “spews data all over the floor” and lacks the security, metadata, and integration necessary for enterprise use. On social media, he dismissed Copilot as “panic mode” rebranding, contrasting it with Agentforce, which he describes as a transformative platform integrated with enterprise data and workflows. Microsoft’s Position Microsoft has largely refrained from engaging directly. Nadella, during a European AI tour, promoted Copilot as “the UI for AI,” positioning it as the interface to a broader AI ecosystem. However, his remarks avoided addressing Benioff’s criticisms, leaving Salesforce’s claims unanswered. Implications for Enterprise AI This debate highlights critical issues for businesses adopting AI technologies. While Salesforce has emphasized pragmatism, acknowledging AI’s uncertainties, Microsoft’s perceived lack of response risks leaving questions unanswered. The stakes are high, with both companies vying for leadership in a rapidly evolving market. What’s Next? How Microsoft responds—or doesn’t—will shape this rivalry’s trajectory. A direct rebuttal could clarify its AI vision, but staying silent risks ceding thought leadership to Salesforce. For businesses navigating the complexities of enterprise AI, understanding these dynamics is essential to making informed decisions. As the AI landscape unfolds, this conflict underscores the competitive importance of securing trust and demonstrating actionable value. For now, the war of words is as much about shaping perceptions as it is about delivering results. 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
PydanticAI: Empowering LLMs with a Robust Agent Framework As the Generative AI landscape evolves at a historic pace, AI agents and multi-agent systems are expected to dominate 2025. Industry leaders like AWS, OpenAI, and Microsoft are racing to release frameworks, but among these, PydanticAI stands out for its unique integration of the powerful Pydantic library with large language models (LLMs). Why Pydantic Matters Pydantic, a Python library, simplifies data validation and parsing, making it indispensable for handling external inputs such as JSON, user data, or API responses. By automating data checks (e.g., type validation and format enforcement), Pydantic ensures data integrity while reducing errors and development effort. For instance, instead of manually validating fields like age or email, Pydantic allows you to define models that automatically enforce structure and constraints. Consider the following example: pythonCopy codefrom pydantic import BaseModel, EmailStr class User(BaseModel): name: str age: int email: EmailStr user_data = {“name”: “Alice”, “age”: 25, “email”: “[email protected]”} user = User(**user_data) print(user.name) # Alice print(user.age) # 25 print(user.email) # [email protected] If invalid data is provided (e.g., age as a string), Pydantic throws a detailed error, making debugging straightforward. What Makes PydanticAI Special Building on Pydantic’s strengths, PydanticAI brings structured, type-safe responses to LLM-based AI agents. Here are its standout features: Building an AI Agent with PydanticAI Below is an example of creating a PydanticAI-powered bank support agent. The agent interacts with customer data, evaluates risks, and provides structured advice. Installation bashCopy codepip install ‘pydantic-ai-slim[openai,vertexai,logfire]’ Example: Bank Support Agent pythonCopy codefrom dataclasses import dataclass from pydantic import BaseModel, Field from pydantic_ai import Agent, RunContext from bank_database import DatabaseConn @dataclass class SupportDependencies: customer_id: int db: DatabaseConn class SupportResult(BaseModel): support_advice: str = Field(description=”Advice for the customer”) block_card: bool = Field(description=”Whether to block the customer’s card”) risk: int = Field(description=”Risk level of the query”, ge=0, le=10) support_agent = Agent( ‘openai:gpt-4o’, deps_type=SupportDependencies, result_type=SupportResult, system_prompt=( “You are a support agent in our bank. Provide support to customers and assess risk levels.” ), ) @support_agent.system_prompt async def add_customer_name(ctx: RunContext[SupportDependencies]) -> str: customer_name = await ctx.deps.db.customer_name(id=ctx.deps.customer_id) return f”The customer’s name is {customer_name!r}” @support_agent.tool async def customer_balance(ctx: RunContext[SupportDependencies], include_pending: bool) -> float: return await ctx.deps.db.customer_balance( id=ctx.deps.customer_id, include_pending=include_pending ) async def main(): deps = SupportDependencies(customer_id=123, db=DatabaseConn()) result = await support_agent.run(‘What is my balance?’, deps=deps) print(result.data) result = await support_agent.run(‘I just lost my card!’, deps=deps) print(result.data) Key Concepts Why PydanticAI Matters PydanticAI simplifies the development of production-ready AI agents by bridging the gap between unstructured LLM outputs and structured, validated data. Its ability to handle complex workflows with type safety and its seamless integration with modern AI tools make it an essential framework for developers. As we move toward a future dominated by multi-agent AI systems, PydanticAI is poised to be a cornerstone in building reliable, scalable, and secure AI-driven applications. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more 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
Google’s Gemini 1.5 Flash-8B: A Game-Changer in Speed and Affordability Google’s latest AI model, Gemini 1.5 Flash-8B, has taken the spotlight as the company’s fastest and most cost-effective offering to date. Building on the foundation of the original Flash model, 8B introduces key upgrades in pricing, speed, and rate limits, signaling Google’s intent to dominate the affordable AI model market. What Sets Gemini 1.5 Flash-8B Apart? Google has implemented several enhancements to this lightweight model, informed by “developer feedback and testing the limits of what’s possible,” as highlighted in their announcement. These updates focus on three major areas: 1. Unprecedented Price Reduction The cost of using Flash-8B has been slashed in half compared to its predecessor, making it the most budget-friendly model in its class. This dramatic price drop solidifies Flash-8B as a leading choice for developers seeking an affordable yet reliable AI solution. 2. Enhanced Speed The Flash-8B model is 40% faster than its closest competitor, GPT-4o, according to data from Artificial Analysis. This improvement underscores Google’s focus on speed as a critical feature for developers. Whether working in AI Studio or using the Gemini API, users will notice shorter response times and smoother interactions. 3. Increased Rate Limits Flash-8B doubles the rate limits of its predecessor, allowing for 4,000 requests per minute. This improvement ensures developers and users can handle higher volumes of smaller, faster tasks without bottlenecks, enhancing efficiency in real-time applications. Accessing Flash-8B You can start using Flash-8B today through Google AI Studio or via the Gemini API. AI Studio provides a free testing environment, making it a great starting point before transitioning to API integration for larger-scale projects. Comparing Flash-8B to Other Gemini Models Flash-8B positions itself as a faster, cheaper alternative to high-performance models like Gemini 1.5 Pro. While it doesn’t outperform the Pro model across all benchmarks, it excels in cost efficiency and speed, making it ideal for tasks requiring rapid processing at scale. In benchmark evaluations, Flash-8B surpasses the base Flash model in four key areas, with only marginal decreases in other metrics. For developers prioritizing speed and affordability, Flash-8B offers a compelling balance between performance and cost. Why Flash-8B Matters Gemini 1.5 Flash-8B highlights Google’s commitment to providing accessible AI solutions for developers without compromising on quality. With its reduced costs, faster response times, and higher request limits, Flash-8B is poised to redefine expectations for lightweight AI models, catering to a broad spectrum of applications while maintaining an edge in affordability. 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
The Rise of Digital Workers: Unlocking a New Era of Opportunity Over the past two years, advancements in artificial intelligence have sparked a revolution in how humans work, live, and connect. While impressive generative AI models have garnered significant attention, a new paradigm of autonomous AI agents is emerging, promising transformative changes to industries and societies alike. Unlike traditional “predictive AI,” which analyzes data for recommendations, and “generative AI,” which creates content based on learned patterns, autonomous AI agents go a step further. These agents operate independently, executing tasks, making decisions, and even negotiating with other agents. This evolution introduces an intelligent digital workforce capable of scaling operations, reducing costs, and enhancing productivity. Consider a large retailer during the holiday season. Instead of relying on human workers or pre-programmed software to address customer inquiries or update inventory, autonomous agents can seamlessly manage customer interactions, monitor stock levels, reorder items, and coordinate shipping—all without human intervention. This level of automation represents a groundbreaking shift, enabling businesses to operate on an unprecedented scale. Expanding the Reach of Digital Labor Autonomous AI agents are breaking traditional barriers of human availability and physical constraints, enabling businesses to scale globally and more efficiently. These digital workers are not limited by geography, opening opportunities previously restricted to specific locations. However, this shift comes with challenges. Ensuring trust, accountability, and transparency in AI systems is critical. Equally important is investing in human-centric skills such as creativity, critical thinking, and adaptability, which remain uniquely human. Sustainability is another concern, as AI-driven technologies place increasing demands on energy and resources. By addressing these issues, societies can unlock the full potential of digital labor while safeguarding the planet and human values. Transforming Everyday Lives Beyond businesses, autonomous agents are poised to transform personal lives. Personalized agents can act as tutors for students, guiding them through their learning journeys. For individuals, these agents can manage everyday tasks, from scheduling appointments to coordinating complex logistics. In healthcare, AI agents are already alleviating administrative burdens on providers. For example, intelligent agents can handle patient communications, monitor progress, and schedule follow-ups, freeing doctors and nurses to focus on complex cases. Such innovations hold the potential to revolutionize patient care and improve outcomes across the board. Navigating Disruption and Change Like any transformative technology, the rise of autonomous agents will bring disruptions. Some industries will struggle to adapt, and jobs will inevitably evolve—or, in some cases, disappear. History shows, however, that technological revolutions often create far more opportunities than they displace. For example, the U.S. workforce grew by over 100 million jobs between 1950 and 2020, many in industries that didn’t exist before. The key lies in preparing workers for new roles through education and training. Autonomous agents are essential in addressing global challenges such as labor shortages and stagnant productivity growth. They amplify human capabilities, driving innovation and boosting economic output. For example, in the third quarter of 2024, U.S. productivity rose by 2.2%, fueled in part by AI advancements. Driving Innovation and Collaboration AI agents are also fostering innovation, sparking the creation of new companies and industries. More than 5,000 AI-focused startups have emerged in the past decade in the U.S. alone. This trend mirrors the technological revolutions driven by past innovations like microchips, the internet, and smartphones. However, effectively harnessing agentic AI requires collaboration among governments, businesses, nonprofits, and academia. Initiatives like the G7’s framework for AI accountability and the Bletchley Declaration emphasize transparency, safety, and data privacy, offering critical guardrails as AI adoption accelerates. A Vision for the Future Autonomous agents represent a powerful force for change, offering unprecedented opportunities for businesses and individuals alike. By leveraging these technologies responsibly and investing in human potential, societies can ensure a future of abundance and progress. As Marc Benioff, CEO of Salesforce, emphasizes, “AI has the potential to elevate every company, fuel economic growth, uplift communities, and lead to a future of abundance. If trust is our north star, agents will empower us to make a meaningful impact at an unprecedented scale.” 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
This advanced cloud solution is hosted on Amazon Web Services’ Top Secret cloud infrastructure. According to Salesforce’s press release, Government Cloud Premium is built with an API-first architecture, enabling agencies to leverage other data sources and systems, including proprietary AI applications, to enhance mission-critical operations.
Clear, accurate sales invoices make the payment process straightforward, helping to reduce customer service inquiries and ensuring a smoother revenue lifecycle. By designing an invoicing process that balances organizational needs with customer convenience, businesses can increase both satisfaction and timely payments.
Not Just Another Insight on Salesforce Agentforce This isn’t your typical rundown of Salesforce Agentforce—the AI innovation everyone’s buzzing about. Instead of merely explaining what it is and calling it a day, we’re diving straight into what matters most: how it can transform operations for nonprofits and educational organizations. If you’re in these sectors and are curious about leveraging Agentforce to drive efficiency, deepen engagement, and scale impact, you’re in the right place. What is Salesforce Agentforce? Introduced at Dreamforce 2024, Salesforce Agentforce is an AI-driven solution within Service Cloud, designed to streamline operations using autonomous, intelligent agents. With no-code setup and pre-built templates, organizations can deploy AI agents tailored to specific industries, like banking, healthcare, or retail. These agents assist in customer interactions, case routing, meeting scheduling, and real-time data gathering. They don’t just automate tasks—they enhance processes by making informed decisions powered by Salesforce’s Customer 360 metadata. Inside Agentforce’s AI-Driven Core Agentforce integrates several cutting-edge tools: For example, you can define an agent’s role with natural language prompts and specify the tasks it will handle, such as donor outreach or event management. Why Nonprofits & Educational Institutions Should Care Agentforce isn’t just for Fortune 500 companies—it’s equally transformative for mission-driven organizations. From automating administrative tasks to delivering personalized experiences, here’s how Agentforce empowers nonprofits and educational institutions: Six Agentforce Use Cases Tailored for Nonprofits & Education To inspire your Agentforce journey, here are six impactful use cases: 1. Automating Volunteer Onboarding Streamline volunteer engagement by automating training resources, scheduling, and shift assignments. Agents can even notify backup volunteers in case of last-minute cancellations. 2. Assessing Student Knowledge Enable adaptive learning by tailoring modules based on performance data. AI agents can identify gaps in knowledge and recommend resources or interventions for students. 3. Aligning Investors with Startups For nonprofits fostering innovation, Agentforce matches investors with startups aligned to their goals, automating onboarding and facilitating collaboration. 4. Coordinating Events & Fundraisers From ticketing and donation tracking to live Q&A sessions, Agentforce simplifies event management while capturing valuable engagement data for future use. 5. Supporting Student Admissions Automate admissions processes by routing inquiries, sending personalized reminders, and tracking application progress. This ensures no step is missed during peak enrollment cycles. 6. Matching Donations to Needs For organizations redistributing goods or funds, Agentforce matches donations to recipients efficiently, summarizing opportunities and streamlining logistics. Ready to Get Started? Agentforce marks a new era of AI-driven operations, empowering nonprofits and educators to maximize impact. With its versatility and ease of use, you can create intelligent workflows that align with your mission. Feeling overwhelmed by where to begin? Our team at Advanced Communities can help you navigate Agentforce and tailor it to your unique needs. Let’s take your organization’s impact to the next level. 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
Navigating Cyber Insurance in an Evolving Threat Landscape The rapidly shifting cyberthreat landscape presents unique challenges for healthcare organizations and underwriters navigating cyber insurance coverage decisions. Cyber liability insurance plays a crucial role in shielding healthcare providers from the mounting costs associated with data breaches and cyberattacks, which now average $9.77 million per incident in the healthcare sector, according to IBM. The Challenges of Retaining Cyber Insurance Healthcare, among other heavily targeted sectors, faces difficulties in securing and maintaining affordable cyber insurance. The constantly evolving threat landscape impacts risk profiles, which drives up premiums and complicates coverage retention. Although year-over-year premium growth plateaued in the U.S. in 2023, 79% of respondents in a Delinea survey still reported increased insurance costs, with 67% experiencing premium hikes between 50% and 100%. As high-profile healthcare cyberattacks and increasing cyber risks persist, navigating the insurance landscape remains a significant challenge. Additionally, the lag in processing claims makes it difficult to anticipate how underwriters will respond to these changing threats. How the Evolving Threat Landscape Impacts Cyber Insurance Obtaining adequate cyber insurance coverage can be challenging in today’s risk-heavy environment. Unlike traditional insurance, where risks remain static, cyber risks constantly evolve to counteract security controls. “Cyber insurance risk adjusters face a unique challenge; unlike fires, which aren’t actively trying to burn you in new ways, cyberthreats are constantly adapting to bypass existing protections,” said Christopher Henderson, senior director of threat operations at Huntress. This continuous adaptation often means that by the time underwriting is complete, a risk assessment may already be outdated. Shifts in the threat landscape are driving changes in cyber insurance questionnaires. While in 2023 insurers focused on remote access tools, vulnerability management, and administrative access controls, the focus in 2024 shifted to include multifactor authentication (MFA) and identity-based attack prevention. This shift highlights the need for organizations to adapt to new requirements in cyber insurance as cybercriminals add new tactics to their playbooks. Adapting Insurance to Emerging Threats As cyberthreat tactics evolve, insurers may adjust policy terms to keep pace with the latest risks. Henderson suggests that insurers could move toward shorter underwriting cycles, possibly even six-month periods, to better align with the rapidly shifting cyber landscape. Mitigating Risk and Controlling Cyber Costs Several factors influence cyber insurance premiums, including organizational size and security posture. For healthcare providers, adhering to industry standards like SOC 2 and ISO 27001 can demonstrate compliance with best practices, improving coverage terms and potentially lowering premiums. Healthcare organizations using the NIST Cybersecurity Framework (CSF) as their primary security standard reported lower premium increases compared to those without this framework, according to a 2024 report by KLAS Research, Censinet, and the American Hospital Association. Henderson emphasizes the importance of layering new strategies with proven, traditional ones: “While staying vigilant against newer tactics like social engineering and identity-based attacks, maintaining consistent, auditable identity verification and MFA protocols remains crucial.” Despite upfront costs, cyber insurance can significantly reduce financial impact during cybersecurity incidents. For example, a 2024 Sophos report found that organizations with cyber insurance saw an average ransomware recovery cost of $2.94 million compared to $3.48 million for those without coverage. Navigating cyber insurance can be complex for healthcare organizations, but careful attention to risks and proactive security measures can help them secure the right coverage at sustainable rates. 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
Could the AI Energy Solution Make AI Unstoppable? The Rise of Brain-Based AI In 2002, Jason Padgett, a furniture salesman from Tacoma, Washington, experienced a life-altering transformation after a traumatic brain injury. Following a violent assault, Padgett began to perceive the world through intricate patterns of geometry and fractals, developing a profound, intuitive grasp of advanced mathematical concepts—despite no formal education in the subject. His extraordinary abilities, emerging from the brain’s adaptation to injury, revealed an essential truth: the human brain’s remarkable capacity for resilience and reorganization. This phenomenon underscores the brain’s reliance on inhibition, a critical mechanism that silences or separates neural processes to conserve energy, clarify signals, and enable complex cognition. Researcher Iain McGilchrist highlights that this ability to step back from immediate stimuli fosters reflection and thoughtful action. Yet this foundational trait—key to the brain’s efficiency and adaptability—is absent from today’s dominant AI models. Current AI systems, like Transformers powering tools such as ChatGPT, lack inhibition. These models rely on probabilistic predictions derived from massive datasets, resulting in inefficiencies and an inability to learn independently. However, the rise of brain-based AI seeks to emulate aspects of inhibition, creating systems that are not only more energy-efficient but also capable of learning from real-world, primary data without constant retraining. The AI Energy Problem Today’s AI landscape is dominated by Transformer models, known for their ability to process vast amounts of secondary data, such as scraped text, images, and videos. While these models have propelled significant advancements, their insatiable demand for computational power has exposed critical flaws. As energy costs rise and infrastructure investment balloons, the industry is beginning to reevaluate its reliance on Transformer models. This shift has sparked interest in brain-inspired AI, which promises sustainable solutions through decentralized, self-learning systems that mimic human cognitive efficiency. What Brain-Based AI Solves Brain-inspired models aim to address three fundamental challenges with current AI systems: The human brain’s ability to build cohesive perceptions from fragmented inputs—like stitching together a clear visual image from saccades and peripheral signals—serves as a blueprint for these models, demonstrating how advanced functionality can emerge from minimal energy expenditure. The Secret to Brain Efficiency: A Thousand Brains Jeff Hawkins, the creator of the Palm Pilot, has dedicated decades to understanding the brain’s neocortex and its potential for AI design. His Thousand Brains Theory of Intelligence posits that the neocortex operates through a universal algorithm, with approximately 150,000 cortical columns functioning as independent processors. These columns identify patterns, sequences, and spatial representations, collaborating to form a cohesive perception of the world. Hawkins’ brain-inspired approach challenges traditional AI paradigms by emphasizing predictive coding and distributed processing, reducing energy demands while enabling real-time learning. Unlike Transformers, which centralize control, brain-based AI uses localized decision-making, creating a more scalable and adaptive system. Is AI in a Bubble? Despite immense investment in AI, the market’s focus remains heavily skewed toward infrastructure rather than applications. NVIDIA’s data centers alone generate 5 billion in annualized revenue, while major AI applications collectively bring in just billion. This imbalance has led to concerns about an AI bubble, reminiscent of the early 2000s dot-com and telecom busts, where overinvestment in infrastructure outpaced actual demand. The sustainability of current AI investments hinges on the viability of new models like brain-based AI. If these systems gain widespread adoption within the next decade, today’s energy-intensive Transformer models may become obsolete, signaling a profound market correction. Controlling Brain-Based AI: A Philosophical Divide The rise of brain-based AI introduces not only technical challenges but also philosophical ones. Scholars like Joscha Bach argue for a reductionist approach, constructing intelligence through mathematical models that approximate complex phenomena. Others advocate for holistic designs, warning that purely rational systems may lack the broader perspective needed to navigate ethical and unpredictable scenarios. This philosophical debate mirrors the physical divide in the human brain: one hemisphere excels in reductionist analysis, while the other integrates holistic perspectives. As AI systems grow increasingly complex, the philosophical framework guiding their development will profoundly shape their behavior—and their impact on society. The future of AI lies in balancing efficiency, adaptability, and ethical design. Whether brain-based models succeed in replacing Transformers will depend not only on their technical advantages but also on our ability to guide their evolution responsibly. As AI inches closer to mimicking human intelligence, the stakes have never been higher. 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. 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