AI Agents - gettectonic.com - Page 9
Generative AI Regulations
25Jun

AI Manipulation

The Future of AI: Convenience and Risk Our lives are on the brink of being transformed by conversational AI agents designed to anticipate our needs, offer tailored information, and perform useful tasks on our behalf. These agents will rely on extensive personal data, including our interests, hobbies, backgrounds, aspirations, personality traits, and political views, all aimed at making our lives more convenient. What then will be the source of AI Manipulation? Advanced AI Agents: The Next Generation These AI agents are becoming increasingly sophisticated. OpenAI recently released GPT-4o, a next-generation chatbot capable of reading human emotions. It does this not only by analyzing the sentiment in written text but also by assessing voice inflections (if spoken to through a mic) and facial cues (if interacting via video). This rapid development signifies the future of computing. Google, for instance, announced Project Astra, an advanced seeing and talking responsive agent designed to interact conversationally while understanding its surroundings. This allows it to provide real-time interactive guidance and assistance. OpenAI’s Sam Altman has predicted that assistive agents will be the killer app for AI. He envisions a future where everyone has a personalized agent acting as a super-competent colleague, knowing everything about their life to take useful actions on their behalf. The Potential Risks-AI Manipulation While this sounds promising, significant risks accompany these advancements. As I wrote in VentureBeat last year, AI agents pose a risk to human agency through targeted manipulation. This risk is particularly acute as these agents become embedded in our mobile devices, which are gateways to our digital lives. These devices provide AI agents with a continuous flow of our personal information, enabling them to learn intimate details about us while filtering the content we receive. Such systems could become powerful tools for interactive manipulation. AI agents equipped with cameras and microphones will react to our environments without explicit prompts, potentially triggering targeted influences based on our activities and situations. Public Perception and Adoption Despite the creepy level of tracking and intervention, I predict that people will embrace this technology. These agents will be designed to make our lives easier, providing reminders, tutoring, and even social coaching. The competition among tech companies will drive rapid adoption, with individuals feeling disadvantaged if they do not use these features. By 2030, these technologies will likely be ubiquitous. The AI Manipulation Problem In my new book, “Our Next Reality,” I discuss how AI agents can empower us with mental superpowers while also serving as tools for persuasion. AI agents, designed for profit, will influence our thoughts and behaviors. They will be more effective than traditional content because they can engage us interactively, using sophisticated techniques based on extensive personal data. These agents will read our emotions with unparalleled precision, adapting their influence tactics in real-time. Without regulation, they could document our reactions to tailor their approaches, making them highly effective at persuasion. The agents’ appearances could also be optimized to maximize their impact on us personally. Feedback Control and the Need for Regulation The technical danger of AI agents lies in their feedback control capabilities. Given an “influence objective,” these agents can continuously adapt their strategies to maximize their impact on us. This ability is similar to heat-seeking missiles adjusting their path in real-time to hit a target. To mitigate this risk, regulators must impose strict limits on interactive conversational advertising, which is the gateway to more dangerous uses of these technologies. If unchecked, this could lead to an arms race among tech companies to develop the most effective conversational ads, ultimately driving misinformation and propaganda. The Urgent Need for Regulatory Action The time for policymakers to act is now. While traditional AI risks like generating misinformation at scale are significant, targeted interactive manipulation poses a far greater threat. Recent announcements from OpenAI and Google highlight the urgency for regulation. An outright ban or stringent limitations on interactive conversational advertising is a crucial first step. Without such measures, we risk allowing AI agents to become powerful tools of manipulation. Conclusion The future of AI holds both promise and peril. As conversational AI agents become integral to our daily lives, we must balance their benefits with the potential for abuse. Regulatory action is essential to ensure these technologies enhance our lives without compromising our autonomy. Louis Rosenberg, PhD, is an American technologist specializing in AI and XR. His new book, “Our Next Reality,” explores the impact of AI on society and is published by Hachette. He earned his PhD from Stanford, was a professor at California Polytechnic, and is currently CEO of Unanimous AI. This piece originally appeared in VentureBeat on 5/17/24. 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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June 25, 2024in Salesforce Einstein
Agentic AI is Here
20Jun

Agentic AI is Here

Embracing the Era of Agentic AI: Redefining Autonomous Systems A new paradigm in artificial intelligence, known as “Agentic Artificial Intelligence,” is poised to revolutionize the capabilities of the known autonomous universe. This cutting-edge technology represents a significant leap forward in AI-driven decision-making and action, promising transformative impacts across various industries including healthcare, manufacturing, IT, finance, marketing, and HR. Agents are the way to go! There is no two ways about this. Looking into the progression of the Large Language Model based applications since last year, its not hard to see that the Agentic Process (agents as reusable, specific and dedicated single unit of work) — would be the way to build Gen AI applications. What is Agentic AI? Agentic Artificial Intelligence marks a departure from traditional AI models that primarily focus on passive observation and analysis. Unlike its predecessors, which often require human intervention to execute tasks, Agentic AI systems possess the autonomy to initiate actions independently based on their assessments. This allows them to navigate much more complex environments and undertake tasks with a level of initiative and adaptability previously unseen. At least outside of sci-fy movies. Real-World Applications of Agentic Artificial Intelligence Healthcare In healthcare, Agentic AI systems are transforming patient care. These systems autonomously monitor vital signs, administer medication, and assist in surgical procedures with unparalleled precision. By augmenting healthcare professionals’ capabilities, these AI-driven agents enhance patient outcomes and streamline care processes. Augmenting is the key word, here. Manufacturing and Logistics In manufacturing and logistics, Agentic AI optimizes operations and boosts efficiency. Intelligent agents handle predictive maintenance of machinery, autonomous inventory management, and robotic assembly. Leveraging advanced algorithms and sensor technologies, these systems anticipate issues, coordinate complex workflows, and adapt to real-time production demands, driving a shift towards fully autonomous production environments. Customer Service Within enterprises, AI agents are revolutionizing business operations across various departments. In customer service, AI-powered chatbots with Agentic Artificial Intelligence capabilities engage with customers in natural language, providing personalized assistance and resolving queries efficiently. This enhances customer satisfaction and allows human agents to focus on more complex tasks. Marketing and Sales Agentic Artificial Intelligence empowers marketing and sales teams to analyze vast datasets, identify trends, and personalize campaigns with unprecedented precision. By understanding customer behavior and preferences at a granular level, AI agents optimize advertising strategies, maximize conversion rates, and drive revenue growth. Finance and Accounting In finance and accounting, Agentic AI streamlines processes like invoice processing, fraud detection, and risk management. These AI-driven agents analyze financial data in real time, flag anomalies, and provide insights that enable faster, more informed decision-making, thereby improving operational efficiency. Ethical Considerations of Agentic Artificial Intelligence The rise of Agentic AI also brings significant ethical and societal challenges. Concerns about data privacy, algorithmic bias, and job displacement necessitate robust regulation and ethical frameworks to ensure responsible and equitable deployment of AI technologies. Navigating the Future with Agentic AI The advent of Agentic AI ushers in a new era of autonomy and innovation in artificial intelligence. As these intelligent agents permeate various facets of our lives and enterprises, they present both challenges and opportunities. To navigate this new world, we must approach it with foresight, responsibility, and a commitment to harnessing technology for the betterment of humanity. 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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June 20, 2024in Marketing Automation, Salesforce Health and Life Sciences Solutions, Salesforce Hospitality Travel and Transportation, Salesforce Public Sector Solutions, Salesforce Sales Cloud

AI Agents

Lessons Learned in the First Year of Developing AI Agents In the first year of working on AI agents, valuable insights emerged from direct collaboration with engineers and UX designers, as they iterated on the overall product experience. The objective was to create a platform for customers to use standard data analysis agents and build custom agents tailored to specific tasks and data structures relevant to their business. This platform integrates connectors to databases like Snowflake and BigQuery with built-in security, supports RAG over a metadata layer describing database contents, and facilitates data analysis through SQL, Python, and data visualization tools. Feedback on the effectiveness of these developments came from both internal evaluations and customer insights. Users from Fortune 500 companies utilize these agents daily to analyze their internal data. Key Insights on AI Agents Additional Insights Further insights on code and infrastructure include: These lessons underscore the importance of focusing on reasoning, iterative improvements to the agent-computer interface, understanding model limitations, and building robust supporting infrastructure to enhance AI agent performance and user satisfaction. 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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June 4, 2024in Salesforce Einstein
AI Agents and Open APIs
16May

AI Agents and Open APIs

How AI Agents and Open APIs Are Unlocking New Rebundling Opportunities While much of the 2023-24 excitement surrounding AI has focused on the capabilities of foundational models, the true potential of AI lies in reconfiguring value creation across vertical value chains, not just generating average marketing content. The Vertical AI Opportunity Most AI hype has centered on horizontal B2C applications, but the real transformative power of AI is in vertical B2B industries. This article delves into the opportunities within vertical AI and explores how companies can excel in this emerging space. Short-Term and Long-Term Strategies in Vertical AI In the short term, many vertical AI players focus on developing proprietary, fine-tuned models and user experiences to gain a competitive advantage. These niche models, trained on domain-specific data, often outperform larger foundational models in latency, accuracy, and cost. As models become more fine-tuned, changes in user experience (UX) must integrate these benefits into daily workflows, creating a flywheel effect. Vertical AI companies tend to operate as full-stack providers, integrating interfaces, proprietary models, and proprietary data. This level of integration enhances their defensibility because owning the user interface allows them to continually collect and refine data, improving the model. While this approach is effective in the short term, vertical AI players must consider the broader ecosystem to ensure long-term success. The Shift from Vertical to Horizontal Though vertical AI solutions may dominate in specific niches, long-term success requires moving beyond isolated verticals. Users ultimately prefer unified experiences that minimize switching between multiple platforms. To stay competitive in the long run, vertical AI players will need to evolve into horizontal solutions that integrate across broader ecosystems. Vertical Strategies and AI-Driven Rebundling Looking at the success of vertical SaaS over the last decade provides insight into the future of vertical AI. Companies like Square, Toast, and ServiceTitan have grown by first gaining adoption in a focused use case, then rapidly expanding by rebundling adjacent capabilities. This “rebundling” process—consolidating multiple unbundled capabilities into a comprehensive, customer-centric offering—helps vertical players establish themselves as the hub. The same principle applies to vertical AI, where the end game involves going vertical to later expand horizontally. AI’s Role in Rebundling The key to long-term competitive advantage in vertical AI lies not just in addressing a single pain point but in using AI agents to rebundle workflows. AI agents serve as a new hub for rebundling, enabling vertical AI players to integrate and coordinate diverse workflows across their solutions. Rebundling Workflows with AI Business workflows are often fragmented, spread across siloed software systems. Managers currently bundle these workflows together to meet business goals by coordinating across silos. But with advances in technology, B2B workflows are being transformed by increasing interoperability and the rise of AI agents. The Rebundling Power of AI Agents Unlike traditional software that automates specific tasks, AI agents focus on achieving broader goals. This enables them to take over the goal-seeking functions traditionally managed by humans, effectively unbundling goals from specific roles and establishing a new locus for rebundling. Vertical AI Players: Winners and Losers The effectiveness of vertical AI players will depend on the sophistication of their AI agents and the level of interoperability with third-party resources. Industries that offer high interoperability and sophisticated AI agents present the most significant opportunities for value creation. The End Game: From Vertical to Horizontal Ultimately, the goal for vertical AI players is to leverage their vertical advantage to develop a horizontal hub position. By using AI agents to rebundle workflows and integrate adjacent capabilities, vertical AI companies can transition from niche providers to central players in the broader ecosystem. This path—going vertical first to then expand horizontally—will define the winners in the AI-driven future of business transformation. 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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May 16, 2024in Data, Salesforce, Technology
UX Principles for AI in Healthcare
10May

Agentic Era of UX

The Agentic Era of UX The future of digital experience has arrived, but it’s fragmenting into countless micro-applications. The missing piece in AI user experience? The experience itself. It’s been almost a year and a half since generative AI burst onto the scene, heralded as transformative. But what have we actually seen in terms of user experience? Many companies released AI-powered summaries or search features, claimed them as revolutionary, and received applause—until the applause faded. The so-called “next era” of tech hasn’t yet delivered on its promise. We were given “the most profound technology since fire,” yet many implementations feel like candles that barely flicker. Many UX designers continue advocating for AI to solve genuine user needs. Technology must serve users, not just exist for its own sake. The core issue now is broader: AI has often been treated as a quick fix rather than a true UX transformation. Where user experience traditionally supports the entire journey, AI is being wedged into small, isolated tasks, losing the holistic perspective. For most companies, AI feels like a string of individual “use cases” rather than a full, cohesive UX meal. Many consulting firms push companies to prioritize use cases in terms of complexity and value, often resulting in chatbots that address a handful of user needs. There are notable exceptions, though. For example, Loom went beyond simple AI features to enhance the user’s entire workflow, supporting end-to-end functionality for video recording, transcription, editing, and even task management. Welcome to the Agentic Era of AI We’re now on the verge of the “agentic” era of AI. Industry leaders are abuzz with the potential of AI agents. OpenAI’s Sam Altman calls agents AI’s “killer function,” while other leaders predict this future is within reach, possibly within 3–18 months. The agentic promise is profound: AI agents, or “agentic workflows,” break down complex tasks into manageable steps, helping users complete intricate projects with autonomy. As Ezra Klein describes, imagine telling an AI to plan your child’s dragon-themed birthday party in Brooklyn, and the agent handles everything from booking to ordering the cake—transforming a casual AI prompt into tangible results. Today’s general-purpose models can’t handle this level of complexity independently. But agentic workflows make this possible by chaining AI actions, allowing systems to execute tasks step-by-step. A Vision for Agentic UX Design’s role in this era is to bring a vision of agentic UX to life. In traditional digital experiences, we build systems that assist users along their journey, but we still expect users to navigate the journey themselves. With an agentic UX, an AI partner supports the user at every step. This vision means UX will be defined by three pillars: Early examples are emerging, like Adobe’s Gen Studio, Intercom’s Copilot, and Dovetail’s Magic Experience, each taking steps toward a future where AI provides ongoing, meaningful support to users. An agentic UX doesn’t necessarily need to label itself “agent-powered.” Dovetail, for instance, offers a suite of “Magic” features where the AI partner plays a supporting role, from summarizing transcripts to highlighting key points. Over time, as AI evolves, these agents will assume greater responsibility in user journeys, shifting from supportive to proactive. Strategically Reinvent for the Agentic Era Adapting to the agentic era presents an opportunity—and a risk for those who ignore it. Currently, organizations are focused on laying the infrastructure for “AI readiness.” While that’s essential, it can obscure the longer-term vision of what’s possible. Until business leaders fully grasp the agentic UX’s potential, it’s up to design to step into a strategic role and make this vision vivid, relatable, and exciting. This requires more than launching a quick proof of concept; it demands a reimagining of digital experience. Here’s a recommended approach: It’s been a challenging year for design, with layoffs and value debates. But with the agentic era approaching, the strategic potential for UX is immense. Now is the time to rally, to guide organizations into a new era of digital experience where users are truly supported every step of the way. 4ox 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

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May 10, 2024in Generative AI, Technology
Rise of AI Agents
06May

Rise of AI Agents

The Rise of AI Agents in Enterprise Automation Rise of AI Agents… It sound a bit like a B grade satire movie. But its not satire or scary. AI Agents, powered by large language models (LLMs), represent a groundbreaking paradigm shift in software. Unlike previous automation technologies, AI agents can reason, collaborate, and act in ways similar to human behavior. This new era of Enterprise AI Agents marks a significant evolution from traditional Robotic Process Automation (RPA), expanding the scope from simple task-level automation to enhancing complex knowledge work. RPA stands for Robotic Process Automation, which uses software bots to automate digital tasks and streamline processes. RPA can help reduce costs and improve efficiency. There are three main types of RPA: attended, unattended, and hybrid From RPA to AI Agents: A Strategic Shift A decade after the emergence of RPA, the enterprise landscape is poised for another transformation with intelligent AI agents. These agents are not merely incremental improvements but a revolutionary technology requiring new skills and tools. They transcend the limitations of RPA, moving beyond rule-based automation to dynamic, context-aware operations. Transitioning from RPA to AI agents is a strategic initiative necessitating executive sponsorship. This shift also offers automation leaders and Centers of Excellence (CoEs) the chance to reimagine their roles as strategic enablers within the enterprise. The Evolution of Enterprise Automation Automating Tasks: RPA RPA gained popularity in the mid-2010s through companies like UiPath, leveraging record-and-playback style UI automation. Despite early skepticism about its fragility, RPA established itself as a cornerstone of low-code business applications. Automating Processes: Intelligent Automation (IA) IA extends beyond RPA by incorporating techniques like API automation and OCR. It signals a shift from point-and-click automation to process automation, often blending coding with low-code tools. However, IA remains rule-based, suitable for structured processes. Automating Work: Intelligent AI Agents AI agents introduce a new agentic planning and execution workflow. They natively understand unstructured data and processes, making them ideal for tasks described in natural language rather than rigid rules. AI agents can self-correct and seek human feedback, enhancing resilience compared to pre-programmed bots. Strategic Applications of AI Agents AI agents expand the possibilities of enterprise automation. While RPA remains effective for repetitive, structured tasks, AI agents bring new capabilities to areas requiring flexible reasoning and decision-making. Tactical Automation AI agents can augment existing RPA workflows, addressing tasks that precede or follow RPA routines. This initial integration helps expand automation’s reach within the enterprise. Standard Decisions in Standard Contexts For work involving standard decisions within platforms like ServiceNow or Salesforce, AI and automation solutions from these vendors are beneficial. These platforms continue to innovate, enhancing their data and process capabilities. Strategic Core Business Workflows The most significant impact of AI agents lies in complex, custom-context tasks central to the enterprise’s operations. Here, built-for-purpose enterprise AI agents can drive substantial value, allowing human workers to focus on more strategic activities. Implementing AI Agents: Steps to Get Started The Urgency of Adopting AI Agents The rapid pace of AI advancements necessitates immediate action. Traditional strategies that plan for future technology must pivot to embrace AI today. Forward-looking companies are already reaping significant benefits from AI, and delaying adaptation risks losing competitive advantage. AI agents are not just the next step in automation; they are a transformative technology redefining enterprise workflows. By acting now, businesses can harness AI agents’ full potential, driving innovation and maintaining relevance in an ever-evolving 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

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May 6, 2024in Salesforce Einstein
Impact of AI Agents Across Key Sectors in 2024
24Apr

Impact of AI Agents Across Key Sectors in 2024

Sophisticated autonomous digital entities are already transforming our lives, industries, and the way we engage with technology. What will be the Impact of AI Agents Across Key Sectors in 2024? While much attention has been given to Generative AI (Gen AI), the next major leap forward comes from AI Agents. This emerging technology is set to revolutionize how we work and interact with the world. How AI Agents Will Shape Daily Life AI Agents: An OverviewAI Agents, also called digital assistants or AI-driven entities, are advanced systems designed to perform tasks and provide services autonomously. They use machine learning, natural language processing, and other AI technologies to understand user needs, solve problems, and complete tasks without direct human intervention. The Impact of AI Agents Across Key Sectors in 2024 Personalization and AssistanceAI Agents are increasingly embedded in our personal and professional routines. By learning our preferences, habits, and needs, they offer personalized recommendations, such as curating music playlists, suggesting films, or creating custom workout plans. Their ability to deliver tailored assistance makes everyday life more seamless and enjoyable. Healthcare AdvancementsIn healthcare, AI Agents are making a significant impact. They can analyze medical records, provide diagnostic insights, and assist with treatment planning. Multi-modal agents even process medical imaging to aid in diagnoses, marking a groundbreaking advancement for both healthcare professionals and patients. Efficiency in BusinessAI Agents are transforming business operations by improving customer service through 24/7 automated chatbots and streamlining processes in supply chain management, human resources, and data analysis. These systems help optimize operations and support more informed decision-making. Education and LearningIn education, AI Agents offer personalized learning experiences tailored to each student’s needs, helping them learn at their own pace. Teachers also benefit, as AI Agents provide insights to customize instruction and track student progress. Enhanced CybersecurityAs cybersecurity threats evolve, AI Agents play a key role in identifying and mitigating risks. They detect anomalies in real-time, helping organizations protect their data and systems from breaches and attacks. Environmental ImpactAI Agents are contributing to sustainability by optimizing energy consumption in buildings, improving waste management, and monitoring environmental changes. Their role in addressing climate change is increasingly critical. Research and InnovationIn fields like drug discovery and climate modeling, AI Agents accelerate research by processing and analyzing vast amounts of data. Their involvement speeds up discoveries and innovation across multiple domains. Impact of AI Agents Across Key Sectors in 2024 In 2024, AI Agents have become much more than just digital assistants; they are driving transformative change across industries and daily life. Their ability to understand, adapt, and respond to human needs makes technology more efficient, personalized, and accessible. However, as AI Agents continue to evolve, it is crucial to consider ethical concerns and promote responsible use. With mindful integration, AI Agents hold the promise of a more connected, sustainable, and innovative future. If you are ready to explore AI Agents in your business, 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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April 24, 2024in Generative AI
2024 AI and Machine Learning Trends
23Dec

2024 AI and Machine Learning Trends

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

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December 23, 2023in Generative AI

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