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Did Google Dethrone ChatGPT
30May

Did Google Dethrone ChatGPT?

Google’s Bard has emerged as a contender in the realm of large language models (LLMs), sparking speculation about its potential to outshine OpenAI’s ChatGPT. This insight explores the validity of this claim and examines the tests and factors that could determine the ultimate victor in this ongoing AI rivalry. Did Google Dethrone ChatGPT? Google’s Gemini 1.5 Pro is a generational leap in terms of Multimodal Large Language Models, or MLLMs, much like GPT-4 was to LLMs back in March 2023. Did Google Dethrone ChatGPT? While initial rumors of Bard’s “dethronement” of ChatGPT surfaced from a single LinkedIn post in February 2024, substantial evidence is required to substantiate such claims. Let’s determine the potential battleground: The Testing Grounds: There’s no singular, universally recognized benchmark for evaluating LLMs. Here are some areas where Google and OpenAI may showcase their AI prowess: Generative Text Quality: Can the LLM generate various creative text formats—such as poems, code, scripts, and emails—while maintaining coherence and factual accuracy? Question Answering: How effectively can the LLM respond to open-ended, challenging, or unconventional questions, drawing on its knowledge base? Following Instructions: Can the LLM adhere to complex instructions and perform tasks requiring multi-step reasoning? Bias Mitigation: Does the LLM demonstrate impartiality in its responses, or does it exhibit traces of prejudice or social stereotypes? Beyond the Tests: While test results offer insights into LLM capabilities, other factors influence their overall impact: Accessibility: How easily can the LLM be accessed by the public? Is there a user-friendly interface or developer API? Real-World Applications: How seamlessly can the LLM be integrated into practical applications like chatbots, virtual assistants, or educational tools? Continuous Learning: How adeptly does the LLM adapt and enhance its performance over time, incorporating new data and user feedback? The Current Landscape: Declaring a definitive winner is challenging. Bard and ChatGPT excel in different domains. Here’s a speculative analysis: Generative Text Quality: Bard may have a slight advantage, leveraging Google’s extensive dataset. Question Answering: ChatGPT might excel in responding to open-ended queries with creativity, while Bard may prioritize factual accuracy. Following Instructions & Bias Mitigation: Both LLMs are continually refining their capabilities in these areas. The Future of LLMs: The landscape of LLMs is dynamic, with Google and OpenAI poised to make significant advancements. Anticipated developments include: Focus on Explainability: Efforts to understand the reasoning behind LLM responses to foster transparency and trust. Bias Mitigation: Strategies to address bias in LLMs for fairer and more inclusive interactions. Specialized LLMs: Development of domain-specific LLMs tailored to fields like medicine or law. Is Google AI better than ChatGPT? Gemini offers a better user experience, with more imagery and website links. Gemini Advanced generates better AI images than ChatGPT Plus. Gemini responses were often set out in a more readable format than ChatGPT’s responses. Gemini was better at generating spreadsheet formulas than ChatGPT. How is Bard better than ChatGPT? Bard has real-time access to the internet through Google Search, allowing it to incorporate the latest information and news into its responses. Trained on a static dataset not updated since 2021, however, ChatGPT can only access external information through plugins, and this functionality is limited. Is Google nervous about ChatGPT? It’s that the technology represents everything Google was afraid artificial intelligence would become. If ChatGPT runs rampant, the search giant fears it could ruin AI adoption for everyone. Since going viral, ChatGPT has demonstrated how generative AI can be user-friendly, practical, and productive. The narrative of ChatGPT’s dethronement may be premature. Bard and ChatGPT are evolving entities, and the ultimate victor will be determined by their ability to navigate future challenges and opportunities. As these LLMs progress, users stand to benefit from access to increasingly sophisticated and beneficial AI 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

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May 30, 2024in Generative AI, Salesforce Einstein
AI in Marketing
29May

AI in Marketing

John Dutton recently posted in his blog about AI “representatives” who talk to you. It’s an interesting look into the “creep” factor potentially in artificial intelligence and certainly provides plenty of food for thought on robots and AI in marketing. Read it here. Summarized below. When the media or the internet shares a look at this wierd generated image talking, its easy to spot. When not flagged, it is getting a little harder to know for sure-is it real or is it Memorex. Unveiling AI in Ukraine Last week, Ukraine’s Ministry of Foreign Affairs introduced Victoriya Shi, a “digital representative” and AI-produced avatar. Shi delivers official statements in videos shared on the Ministry’s online social channels. According to Ukrainian Foreign Minister Dmytro Kuleba, Shi was created to “save time and resources” for diplomats. Given the ongoing conflict in Ukraine, this rationale seems reasonable. However, the introduction of such an AI avatar raises questions about the future and the potential for dystopian developments. A key concern is the ease of deepfaking an already artificial persona. This challenge has been addressed by the MFA through a smart yet simple solution: a QR code in the corner of each video that directs viewers to the official text version of the announcement on the Ministry’s website. It’s worth noting that the official statements themselves are not AI-generated, which could set a worrying precedent. While the Ukrainian version’s reception is unknown, the English version of Victoriya Shi struggles to escape the “uncanny valley” of artificial humans. Her sign-off, “I look forward to our fruitful cooperation,” has an eerie, robotic undertone. This unsettling impression might not be entirely negative. Navigating the Age of AI We are deeply entrenched in the Age of AI, where trust has become a scarce commodity. The concept of “fake news” emerged well before generative AI, gaining prominence in late 2016 with the rise of certain political figures. A search on Google Trends reveals the sudden spike in terms like “fake news” and “post-truth” during that period. With AI’s potential to create convincing deepfakes, the challenge of distinguishing real from fake is intensifying. A recent incident in Hong Kong saw an employee deceived by an AI-generated video, leading to a $25 million fraud. This highlights the need for secure credentialing, especially in large organizations and potential metaverse meetings. However, in-person meetings remain immune to such digital deceptions. AI’s Role in Authenticity Ironically, AI might help combat its own deceptions. OpenAI’s recent collaboration with the Coalition for Content Provenance and Authenticity (C2PA) aims to develop tools for identifying AI-generated content. As deepfakes become more sophisticated, the absence of C2PA authentication could become a red flag. If this leads to a heightened skepticism towards digital media, it might not be entirely negative. AI could bolster our defenses against scams, encouraging a healthy suspicion of the digital content we consume. The Balance of Authenticity and Truth The distinction between authenticity and truth is crucial. A government-created AI avatar can be fake in its artificiality but still deliver authentic, official statements. As generative AI advances, we must fine-tune our skepticism. Victoriya Shi’s name reflects Ukraine’s hope for “victory” and the integration of AI (“Shi” in Ukrainian). The war may ultimately hinge on intelligent tech use rather than sheer military might. Update and Reflections Following the newsletter’s release, it was revealed that WPP, the world’s largest ad agency network, nearly fell victim to a deepfake scam, with the CEO’s voice being replicated by AI. The Dystopia/Utopia Dichotomy The generative AI revolution has begun, and its trajectory could lead to either a utopian or dystopian future. My novel, “2084,” explores a world where life appears superficially perfect, masking underlying issues. Artistic AI Innovations One of my book’s main characters is a sculptor, a profession I initially believed immune to AI. However, Monumental Labs, founded in 2022, uses “sensors and AI” to produce sculptures at a fraction of traditional costs. This reality mirrors the AI-driven world imagined in “2084.” Genetic Modifications and Luxury Fresh Del Monte’s Rubyglow® pineapple, an ultra-premium, genetically modified fruit, exemplifies the future of designer foods. My novel envisions similar advancements with patented food items and drone-pollinated plants. The Challenger Mindset Adam Morgan, an expert in the challenger brand mindset, emphasizes the importance of maintaining a challenger attitude regardless of market position. Companies like Netflix exemplify this, adapting and thriving in a competitive landscape by retaining a challenger’s drive. The Right to Repair and Brand Identity The US Government Accountability Office highlights the “softwareification” of cars, making independent repairs difficult. Similarly, Apple’s restrictive policies on iPhone repairs underline the broader trend of manufacturers controlling repair markets. Cult of Brand Identity The Gray Area podcast discusses how modern consumers interact with brands, focusing on identity over product quality. This shift underscores the evolving landscape of commercial competition and consumer behavior. 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 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more

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May 29, 2024in Generative AI, Salesforce Einstein
Securing SaaS
26May

Securing SaaS

Obsidian Security recently discussed the complexity of enforcing Single Sign-On (SSO) within Salesforce and frequently encountering misconfigurations. Notably, 60% of Obsidian’s customers initially have local access without Multi-Factor Authentication (MFA) configured for Salesforce, highlighting a significant security gap that Obsidian diligently works to secure. Securing SaaS. The Hidden Vulnerability Application owners who manage Salesforce daily often remain unaware of this misconfiguration. Despite their deep knowledge of Salesforce management, local access without MFA presents an overlooked vulnerability. This situation raises concerns about the security of other SaaS applications, especially those without developed expertise or knowledge. If you have concerns about your configuration, Tectonic can help. Attacker Focus and Trends Attackers have historically targeted the Identity Provider (IdP) space, focusing on providers like Okta, Microsoft Entra, and Ping. This strategy offers maximal impact, as compromising an IdP grants broad access across multiple applications. Developing expertise to breach a few IdPs is more efficient than learning the diverse local access pathways of numerous SaaS vendors. Over the past 12 months, nearly 100% of the breaches that required Obsidian’s intervention through CrowdStrike or other incident response partners were IdP-focused. Notably, 70% of these breaches involved subverting MFA, often through methods like SIM swapping. In instances where local access bypasses the IdP, 95% of the time it lacks MFA. Recent discussions around Snowflake have brought attention to “shadow authentication,” defined as unsanctioned means to authenticate a user within an application. Obsidian Security has observed an increase in brute force attacks against SaaS applications via local access pathways over the last two weeks, indicating a growing awareness of this attack vector. Future Expectations Attackers continually seek easy and efficient pathways. Over the next 12 months, local access or shadow authentication is expected to become a major attack vector. Organizations must proactively secure these pathways as attackers shift their focus. What You Can Do How Obsidian Helps Salesforce Security partners offers robust solutions to address these challenges: By leveraging partner capabilities, organizations can enhance their security posture, protecting against evolving threats targeting local access and shadow authentication. The post “The Growing Importance of Securing Local Access in SaaS Applications” appeared first on Obsidian Security. 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 26, 2024in Salesforce, Salesforce Einstein, Snowflake
Einstein Generative AI Added to Service Cloud
24May

Einstein Generative AI Added to Service Cloud

Salesforce to Enhance Service Cloud with New AI Tools and Broaden Automated Customer Conversations Salesforce is set to roll out more Einstein 1 generative AI tools for Service Cloud users in June and October. But the big news? More places to deploy automated customer conversations are on the way. Unified Conversations for WhatsApp and Line Yesterday, Salesforce unveiled Unified Conversations for WhatsApp. This feature automates bot responses to customer queries related to targeted marketing messages on the popular messaging app. And that’s not all—later this year, Salesforce plans to support Line, the widely used messaging app in Japan. These services leverage Salesforce’s Einstein 1 generative AI platform. The bots aggregate structured and unstructured CRM, product, service, and other data via Salesforce Data Cloud to generate personalized responses. The new features allow these conversations to be routed to the channels where a Salesforce user’s customers are most active online. Expanding Channel Support Salesforce also plans to introduce a “bring your own channel” connector to support digital channels not natively covered by the platform. Think TikTok, Discord, and South Korea’s KakaoTalk, said Ryan Nichols, chief product officer for Salesforce Service Cloud. “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just do a great job of delivering customer service, but actually growing your business,” Nichols explained. Conversation Mining and Revenue Opportunities Salesforce Einstein Conversation Mining, currently in beta, aggregates conversations across customer channels to surface insights on the topics where customers need help. The goal is to turn inbound customer service from a cost center into a revenue center—a dream that speakers and vendors at conferences like Dreamforce and ICMI have been floating for years. Traditionally, performance metrics such as time-to-answer and hold-time reduction have pushed agents to minimize call durations. However, the integration of generative AI could transform this dynamic. Constellation Research analyst Liz Miller, who has previously been skeptical, now sees generative AI as a potential game-changer. Armed with data, bots, and their copilot counterparts, agents could save time and access the right information to up-sell customers during service engagements. Nichols hinted that Salesforce is working on up-sell automation features for contact center service bots, which might be unveiled later this year. A Leap Forward for Contact Centers Copilot-type technologies for contact centers could be the breakthrough needed to enable human agents to generate revenue during service interactions. “Contact center leaders have been trying to etch out a space of strategic importance for themselves in the business that isn’t just ‘how do we get angry people off the phone?’” Miller said. Einstein Generative AI Added to Service Cloud Generative AI tools can eliminate the mundane, repetitive tasks that consume much of contact center agents’ time. Miller added, “If they no longer had to summarize the call, and they could actually go to the next call? [Generating revenue] sounds really big, and it sounds really ridiculous, but if we took all the garbage off of these people’s plates that no one wants to do, we give them an awful lot of time to actually be better mouthpieces for their organizations.” In short, Salesforce is gearing up to transform customer service into a more efficient, revenue-generating machine with a little help from generative AI. And who knows, maybe your next customer service bot will be better at upselling you than your favorite barista. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 24, 2024in Einstein Insights, Salesforce Einstein, Salesforce Service Cloud
Generative AI and Service Cloud
23May

Generative AI and Service Cloud

Salesforce Service Cloud users are set to receive more Einstein 1 generative AI tools in June and October. A key development is the expansion of automated customer conversations across more sales and marketing platforms. Generative AI and Service Cloud family of tools is growing. This insight aims to uncover the numerous use cases of generative AI in the modern contact center. We’ll help you understand how generative AI can fast track your contact center’s efficiency, improve data analysis capabilities, streamline QA and coaching processes, and make customers’ experiences better.  Today, Salesforce launched Unified Conversations for WhatsApp, which automates bot responses to customer inquiries related to targeted marketing messages on the popular messaging app. Additionally, Salesforce plans to extend support to Line, a messaging app popular in Japan, later this year. These services are built on Salesforce’s Einstein 1 generative AI platform. The platform’s bots aggregate structured and unstructured CRM, product, service, and other data through Salesforce Data Cloud to generate personalized responses. These new features enable conversations to be routed to the digital channels where a Salesforce user’s customers are the most active. And to move omnichannel as customers needs change. Salesforce is also introducing a “bring your own channel” connector to support digital channels not natively covered by the platform. Current examples might include TikTok, Discord, and South Korea’s KakaoTalk, according to Ryan Nichols, Chief Product Officer for Salesforce Service Cloud. Generative AI and Service Cloud “It’s about getting data from all your conversations with customers from Service Cloud into Data Cloud and using that to not just deliver excellent customer service, but also grow your business,” Nichols said. Salesforce Einstein Conversation Mining, a Service Cloud feature currently in beta, aggregates conversations across customer channels to surface insights on the topics customers need help with. This aims to turn inbound customer service from a cost center into a revenue center, a goal long pursued at conferences like Dreamforce and ICMI. This massive change drives more than revenue, it drives ROI. Performance metrics such as time-to-answer and hold-time reduction have traditionally pressured agents to minimize call duration to retain their jobs. Now Salesforce is going to help them. While some skeptics question if generative AI can achieve this ambitious goal, Constellation Research analyst Liz Miller suggests it might be possible. Having previously managed a contact center herself, Miller recognizes the transformative potential of generative AI. With the aid of data, bots, and copilot counterparts assisting humans, agents could save time and access the right information to upsell customers during service engagements. Here are some of the ways Generative AI will change customer service forever. 1. Monitor and Ensure Compliance Maintaining compliance is crucial for fostering customer trust, preserving a positive brand image, and avoiding hefty privacy and compliance fines. In a contact center, compliance mistakes can quickly escalate into costly lawsuits and revenue losses. Generative AI allows your compliance team to proactively manage compliance by quickly identifying trends and addressing issues in real time. Instead of waiting for a compliance issue to escalate, you can fine-tune your AI model to provide compliance insights whenever necessary. For instance, you can ask: This approach offers more comprehensive insights than scorecards, which often lack context and accuracy. Generative AI’s analytical capabilities provide actionable insights to improve compliance across your contact center. 2. Get Insights About Your Call Center Performance at a Glance Generative AI language models make it easier than ever to gain insights into your contact center’s performance. Simply ask the model for the information you need. For example, you can inquire about the real-time average handling time (AHT) by asking, “What is the average handling time today?” But that’s just the beginning. With an advanced language model, you can compare metrics across different quarters or generate ideas for coaching plans by asking for each agent‘s strengths and weaknesses and suggestions for improvement. 3. Automate Post-Call Work Generative AI assistants can act as real-time notetakers, summarizing 100% of calls and freeing agents from manual note-taking. This automation makes after-call work effortless, generating comprehensive and compliant notes with a single click. 4. Capture Coachable Moments Easily Incorporating real-world coachable moments into your sessions is essential for tangible performance improvements. Generative AI can identify areas where agents typically struggle without requiring hours of call listening and note-checking. Traditional methods mean compromising on the specificity of coaching due to time constraints, especially when managing large teams. Generative AI solutions, however, enable call center managers to obtain detailed insights about each agent’s performance quickly. This allows for personalized coaching plans that address individual shortcomings efficiently. You can ask: 5. Improve Decision Making With Efficient Root-Cause Analysis Effective decision-making can transform your contact center. However, many managers struggle to identify the root causes of performance issues. Generative AI algorithms can analyze vast amounts of data and customer interactions, uncovering patterns and trends in customer and agent behavior. These insights help pinpoint the issues most impacting performance and customer satisfaction, allowing you to make informed decisions. The process is nearly fully automated, freeing your team from time-consuming data collection tasks. 6. Reduce Manual Work and Focus on Improvement Improving contact center performance requires extensive data, which is resource-intensive to collect manually. Generative AI simplifies this by analyzing customer interactions and providing actionable insights on demand. This saves time and money, allowing you to focus on improvements that deliver a higher ROI. 7. Scale What Works Discovering and scaling best practices is essential for team-wide success. Generative AI and Natural Language Processing (NLP) models can analyze customer interactions to identify effective strategies and coaching opportunities. For example, if a representative handles challenging situations well, AI can generate tips for other team members based on these successful interactions. Generative AI can identify top-performing agents and analyze their calls to extract best practices, providing a more comprehensive approach than focusing on a single agent. Queries you might use include: 8. Generate Agent Scripts Generative AI enables you to draft and fine-tune agent scripts for various customer interactions. Instead of relying

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May 23, 2024in Generative AI, Salesforce Data Cloud, Salesforce Einstein, Salesforce Service Cloud
Connections and State of AI
21May

Connections and State of AI

Salesforce Unveils Latest State of Marketing Study Ahead of Annual Connections Conference CHICAGO, May 21, 2024 – As Salesforce gears up for its annual Connections marketing and commerce conference, the company has released the ninth edition of its State of Marketing study. This year’s conference, themed around AI, marketing, and commerce, sets the stage for a deep dive into the future of these interconnected fields. AI Takes Center Stage: The study, drawing insights from over 4,800 marketers across 29 countries, reveals that AI is both the top implementation priority and the biggest challenge for marketers in the coming year. An impressive 63% of marketers currently use generative AI, with an additional 35% planning to adopt the technology within the next 18 months. Key AI applications identified include automating customer interactions, generating content, analyzing performance, automating data integration, and driving real-time best offers. Regional Variations: While AI is a global priority, regional differences are notable. In the US, AI implementation ranks second to improving ROI/attribution, whereas in the UK, it doesn’t even make the top five priorities. Despite these differences, both US and UK marketers cite AI implementation as their third greatest challenge. Countries prioritizing AI include South Korea, UAE, Argentina, Germany, Italy, Japan, Poland, Portugal, and Spain. Interestingly, AI does not feature in the top five priorities for India and Singapore. Challenges in AI Implementation: Across the board, data exposure and leakage are the top concerns related to generative AI, followed by a lack of necessary data, unclear strategy or use cases, fear of inaccurate outputs, and concerns about copyright/IP issues. These challenges vary by industry. For instance, government and media/entertainment sectors worry about AI job displacement, while other sectors focus on biases, brand adherence, and general distrust of AI. Data Integration Struggles: Marketers use an average of nine different tactics to capture customer data, including customer service interactions (88%), transaction data (82%), mobile apps (82%), web registrations (82%), and loyalty programs (80%). However, integrating this data into a unified system remains a significant challenge. Only 31% of marketers are fully satisfied with their ability to unify customer data, and many still rely on IT support for basic marketing tasks. The Personalization Paradox: Despite technological advances, fewer than six in 10 marketers can fully personalize familiar channels like email and mobile messaging. This gap highlights the ongoing struggle to meet rising customer expectations for personalized experiences. Steve Hammond, EVP and GM of Marketing Cloud at Salesforce, emphasizes the importance of personalization at scale: “Customers want to feel like they’re more than just a number. They want relevant experiences that create relationships. But personalization is still a challenge, especially at massive scale.” Looking Ahead: The findings from the State of Marketing study will undoubtedly fuel discussions at Connections. While the potential of AI is exciting, the need for a solid data foundation is critical for realizing its benefits. As the conference unfolds, diginomica’s Jon Reed will be on the ground in Chicago, providing updates on key insights and discussions. About Salesforce: Salesforce is the leading AI CRM, empowering companies to connect with their customers through a unified platform that combines CRM, AI, data, and trust. For more information, visit www.salesforce.com. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 21, 2024in Salesforce, Salesforce Einstein
Salesforce Summer 24 Service Release
20May

Salesforce Summer 24 Service Release

Service Salesforce Summer 24 Service Release. Check out new features that enable customer service agents to work faster and more productively across customer service channels. Salesforce Summer 24 Service Release 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 20, 2024in Salesforce Service Cloud, Unified Knowledge
Patterns for Trust in AI
20May

Patterns for Trust in AI

The advent of AI has introduced a layer of complexity to the concept of trust, intertwining technology with societal and individual concerns in various ways. Patterns for Trust in AI address some of these concerns. Ultimately, this erosion of trust poses formidable obstacles to innovation and responsible development within teams. To foster trust and mitigate these challenges, the adoption of design patterns emerges as a viable solution: Design patterns encapsulate solutions to common problems in a manner that’s easily replicable by others, offering a framework for creating trustworthy services. While design patterns streamline user experiences, they should also introduce a judicious level of friction to: Like Related Posts 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more 50 Advantages of Salesforce Sales Cloud According to the Salesforce 2017 State of Service report, 85% of executives with service oversight identify customer service as a Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more

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May 20, 2024in Generative AI, Salesforce Einstein, Salesforce Optimization
AI Misconceptions Dispelled
19May

AI Misconceptions Dispelled

The recent launch of GPT-4o (“o” for “omni”) has captivated everyone with its seamless human-computer interaction. Capable of solving math problems, translating languages in real-time, and even answering queries in a human voice with emotions, GPT-4o is a game-changer. Within hours of its debut, shares of Duolingo, the popular language EdTech platform, plummeted by 26% as investors perceived GPT-4o as a potential threat. But what AI Misconceptions Dispelled, would prevent this? Fears about AI are widespread. Many believe it will become so advanced and efficient that employing humans will be too costly, potentially leading to mass unemployment. Over the past year, it has become clear that artificial intelligence (AI) is among the most disruptive forces in business. AI promises efficiency and speed but also raises concerns about bias and ethics. In a candid conversation on Mint’s new video series All About AI, Arundhati Bhattacharya, Chairperson and CEO of Salesforce India, dispels these fears and discusses bridging the generation gap and making Salesforce a Great Place to Work. Forging Unity and Vision “When I came in, there were disparate groups—sales and distribution, technology and products, support and success. Each group had its leaders, but nobody was bringing them together to create one Salesforce vision and ensure that each group developed the Salesforce DNA,” Arundhati reflects on her April 2020 arrival. She underscored Salesforce’s values-driven approach, highlighting the significance of Trust, Customer Success, Innovation, Equality, and Sustainability. Under Arundhati’s leadership, Salesforce India has risen from 36th to 4th on the Great Places to Work list. Navigating AI Skepticism AI advancements are profoundly shaping industries and humanity’s future. According to Frost & Sullivan’s “Global State of AI, 2022” report, 87% of organizations see AI and machine learning as catalysts for revenue growth, operational efficiency, and better customer experiences. A 2023 IBM survey found that 42% of large businesses have integrated AI, with another 40% considering it. Furthermore, 38% of organizations have adopted generative AI, with an additional 42% contemplating its implementation. Despite the excitement around AI, skepticism remains. Arundhati offers insights on addressing this skepticism and using AI to benefit society. She suggests a balanced approach, noting that every significant technological change has sparked similar fears. Arundhati argues that AI won’t necessarily lead to massive unemployment, given humanity’s ability to adapt and evolve. Amidst India’s socio-economic challenges, Arundhati sees AI as a potent tool for positive change. She cites examples like the Prime Minister’s Jan Dhan Yojana, where AI-enabled solutions facilitated broader financial inclusion. “Similarly, AI can greatly improve services in state hospitals where doctors are overworked. AI can gather patient symptoms and present an initial diagnosis, allowing doctors to focus on more critical aspects. The technology is also being used to check sales conversations for accuracy in insurance, ensuring compliance and reducing mis-selling,” she elaborates. Driving Productivity through AI Integration Improving productivity in India is a pressing issue, and AI can effectively bridge this gap. However, the term “AI” is often overused and misunderstood. People need to approach AI initiatives with intentionality and focus. First, determine the use cases for AI, such as improving productivity, gaining customer mindshare, or enhancing customer experience. Once that is clear, ensure your organization is structured to provide the right inputs for AI, which involves having a robust data strategy. Tools like Data Cloud can help by integrating various data sources without copying the data and extracting intelligence from them. Lastly, securing buy-in from employees is crucial for successful AI implementation. Addressing their concerns, communicating the potential risks, and aligning everyone toward the same goal is essential. Securing the Future: Addressing AI Security Concerns As AI technologies advance, concerns about their security and potential misuse also rise. Threat actors can exploit sophisticated AI tools intended for positive purposes to carry out scams and fraud. As businesses rely more on AI, it is vital to recognize and protect against these security risks. These risks include data manipulation, automated malware, and abuse through impersonation and hallucination. To tackle AI security challenges, consider prioritizing cybersecurity measures for AI systems. Salesforce makes substantial investments in cybersecurity daily to stay ahead of potential threats. “We use third-party infrastructure with additional security layers on top. Public cloud infrastructure provides multiple layers of security, much like a compound with perimeter, building, and apartment security,” Arundhati explains. Empowering the Next Generation Workforce and Fostering Innovation Transitioning from her previous role as Chairperson of the State Bank of India to leading Salesforce India, Arundhati acknowledges the generational shift in workforce dynamics. She emphasizes understanding and catering to the evolving needs and aspirations of a younger workforce, focusing on engagement and fulfillment beyond monetary incentives. “Salesforce has a strong giving policy called one by one by one, where we give 1% of our profit, products, and time to the nonprofit sector. This resonates with the younger workforce, making them feel engaged and fulfilled.” Through a dedicated startup program, Salesforce fosters a collaborative ecosystem where startups can leverage resources, tools, and connections to thrive and succeed. Arundhati’s stewardship of Salesforce India epitomizes a transformative leadership approach anchored in values, innovation, and community empowerment. Under her leadership, Salesforce India continues to chart a course toward sustainable growth and inclusive prosperity, poised to redefine the paradigm of corporate success in the digital age. Like1 Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 19, 2024in Generative AI, Salesforce Einstein
AI Design Beyond the Chatbot
17May

AI Design Beyond the Chatbot

As AI continues to advance, designers, builders, and creators are confronted with profound questions about the future of applications and how users will engage with digital experiences. AI Design Beyond the Chatbot. Generative AI has opened up vast possibilities, empowering people to utilize AI for tasks such as writing articles, generating marketing materials, building teaching assistants, and summarizing data. However, alongside its benefits, there are challenges. Sometimes, generative AI produces unexpected or biased responses, a phenomenon known as hallucination. In response, approaches like retrieval augmented generation (RAG) have emerged as effective solutions. RAG leverages a vector database, like SingleStore, to retrieve relevant information and provide users with contextually accurate responses. AI Design Beyond the Chatbot Looking ahead, the evolution of AI may lead to a future where users interact with a central LLM operating system, fostering more personalized and ephemeral experiences. Concepts like Mercury OS offer glimpses into this potential future. Moreover, we anticipate the rise of multimodal experiences, including voice and gesture interfaces, making technology more ubiquitous in our lives. Imran Chaudhri’s demonstration of a screen-less future, where humans interact with computers through natural language, exemplifies this trend. However, amidst these exciting prospects, the current state of AI integration in businesses varies. While some are exploring innovative ways to leverage AI, others may simply add AI chat interfaces without considering contextual integration. To harness AI effectively, it’s crucial to identify the right use cases and prioritize user value. AI should enhance experiences by reducing task time, simplifying tasks, or personalizing experiences. Providing contextual assistance is another key aspect. AI models can offer tailored suggestions and recommendations based on user context, enriching the user experience. Notion and Coda exemplify this by seamlessly integrating AI recommendations into user workflows. Furthermore, optimizing for creativity and control ensures users feel empowered in creation experiences. Tools like Adobe Firefly strike a balance between providing creative freedom and offering control over generated content. Building good prompts is essential for obtaining quality results from AI models. Educating users on how to construct effective prompts and managing expectations regarding AI limitations are critical considerations. Ultimately, as AI becomes more integrated into daily workflows, it’s vital to ensure seamless integration into user experiences. Responsible AI design requires ongoing dialogue and exploration to navigate this rapidly evolving landscape effectively. 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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May 17, 2024in Generative AI, Salesforce Einstein
Otter AI S-Docs and Salesforce
17May

Otter AI S-Docs and Salesforce

Numerous vendors in the enterprise software market are currently emphasizing their AI capabilities, envisioning a future where AI can address a wide array of global challenges, from healthcare to climate change. While the realization of these claims remains uncertain, the practical and impactful applications of AI in everyday scenarios often go unnoticed. There exists ample opportunity for leveraging AI tools that are readily available and require minimal setup to enhance efficiency. Otter AI S-Docs and Salesforce. One such example is S-Docs, a document automation vendor integrated natively on the Salesforce platform, which is harnessing Otter.ai, an AI transcription service, to revolutionize its sales process and product development. S-Docs is seamlessly integrating Otter.ai into its digital collaboration tools, enabling automatic transcription during sales calls. This not only aids sales representatives in navigating diverse dialects but also streamlines post-call administrative tasks, prompting quicker action. Moreover, the product development team at S-Docs is leveraging Otter.ai to analyze the transcribed content from sales calls and incorporate insights into its product feedback loop. This integration was sparked by S-Docs’ CTO, Anand Narasimhan, who discovered Otter.ai through a LinkedIn connection and recognized its potential value for the business. Initially used during team calls and sprint reviews, Otter.ai’s high transcription accuracy and insightful summaries impressed Narasimhan and his colleague, Keith Bossier, VP of Sales at S-Docs. Subsequently, Otter.ai was adopted by the sales and customer success teams, offering benefits that surpassed those of their previous provider, Gong. For the sales team, Otter.ai significantly reduces the administrative burden by providing real-time transcriptions, catch-all summaries, and key takeaways from meetings. This facilitates quicker follow-ups and enhances the overall customer experience. Buoyed by the success in sales, S-Docs is exploring avenues to expand the use of Otter.ai across its business. Bossier envisions leveraging transcripts from sales calls for onboarding new representatives, while Narasimhan explores integrating the captured content into the product development cycle. Additionally, they are collaborating with Otter.ai to introduce automated action items directly into the S-Docs platform, further streamlining operations and enhancing efficiency. As S-Docs continues to innovate and optimize its processes with Otter.ai, it exemplifies the tangible benefits of leveraging AI in practical business scenarios. 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 17, 2024in Salesforce, Salesforce Einstein, Salesforce Optimization, Salesforce Sales Cloud
Summer 24 The AI Release
17May

Summer 24 The AI Release

Salesforce Unveils Summer 2024 Release with Generative AI at the Forefront Salesforce has announced its Summer 2024 release, featuring generative AI (GenAI) as a key highlight. Set to be generally available on June 17, 2024, this release promises enhanced productivity and access to large language models (LLMs) on an open platform. Read on to see why we call Summer 24 the AI release. Key Features of the Summer 2024 Release 1. Bring Your Own LLM Expansion 2. Slack AI 3. Zero Copy Integration with Amazon Redshift 4. Vector Database 5. Data Cloud for Commerce 6. Digital Wallet Enhanced Security with Einstein Trust Layer The Einstein Trust Layer ensures enhanced protection for customer and company data, making the new features more secure. Upcoming Pre-Summer Releases In addition to the major features coming in June, Salesforce has already introduced several innovations: Unified Knowledge Solution Salesforce and Vonage Partnership Conclusion Salesforce’s Summer 2024 release is packed with generative AI enhancements, robust integrations, and new tools aimed at boosting productivity, security, and data insights. With features gradually rolling out and pre-summer innovations already available, Salesforce continues to lead in delivering cutting-edge AI solutions to its users. 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 17, 2024in Einstein Insights, Generative AI, Salesforce, Salesforce Einstein, Unified Knowledge
Mastercard Salesforce Integration
16May

Mastercard Salesforce Integration Announced

As consumers seek easier and safer shopping experiences, Mastercard (NYSE: MA) and Salesforce (NYSE: CRM) today announced a new integration to enhance trust across the ecosystem, helping customers speed up the resolution of transaction disputes, and reduce costs associated with resolving them. Mastercard Salesforce Integration. Disputes and chargebacks, where a consumer notices a transaction they don’t recognise and requests a chargeback from their bank, represent a significant challenge to the entire payments industry. Projections suggest that by 2026 there could be 337 million chargebacks annually, an increase of 42% from 2023 levels1. The integration will streamline the way issuers, like banks and other financial institutions, view and manage transaction data, such as disputes and decisions. It will enable a quicker, more efficient and transparent response to dispute inquiries. The partnership will integrate Salesforce’s Financial Services Cloud (FSC) with Mastercard’s dispute resolution services, providing a powerful one-stop-shop for intake, managing disputes, reporting and preventing chargebacks. Mastercard’s services include Ethoca Alerts, which provides near real-time notifications when a financial institution raises a chargeback and Ethoca Consumer Clarity, enabling the provision of rich merchant and purchase insights to issuer back-office teams. The data from these services is now being fed into FSC so that every bank agent and team member working on a dispute has more visibility from start to finish and delivers the best customer experience. FSC is powered by the Einstein 1 Platform, which unifies customer relationship management (CRM), AI, merchant and consumer data, development and security capabilities into a single, comprehensive platform. Johan Gerber, Executive Vice President, Security and Cyber Innovation at Mastercard said: “Technology is helping to speed up and improve the checkout experience, especially when shopping online. However, every disputed transaction can create stress for the consumer as well as resource pressures and increased costs for merchants and financial institutions. Through this partnership, we are adding to the tools that make it easier and faster for banks and merchants to resolve disputes, further enhancing trust in the ways they choose to pay.” Eran Agrios, Senior Vice President and General Manager for Financial Services at Salesforce said: “Our partnership with Mastercard is a testament to our shared vision of using trusted data and innovative technology to streamline processes and deliver great customer experiences through the Einstein 1 Platform. Together with the Mastercard team, we’re reimagining the entire transaction dispute process, bringing together the power of Salesforce’s CRM, data, and AI with Mastercard’s dispute resolution, to deliver an end-to-end solution that will benefit both our joint customers.” Availability The integration is available today for Salesforce FSC customers. More information about the Transactions Dispute Management offering is available on salesforce.com. Information on Mastercard’s Ethoca solutions is available on ethoca.com.  Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Health Cloud Brings Healthcare Transformation Following swiftly after last week’s successful launch of Financial Services Cloud, Salesforce has announced the second installment in its series Read more

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May 16, 2024in Einstein 1 Platform, Salesforce, Salesforce Einstein, Salesforce Optimization
Einstein Web Recommendations
16May

Einstein Web Recommendations

Einstein Web Recommendations leverage Einstein’s capabilities to analyze user behavior, construct preference profiles, and deliver personalized content tailored to each website visitor. Utilize application scenarios to fine-tune recommendations according to your specific business rules. Web Recommendations are provided through two methods: a JSON response or HTML/JS. While the JSON response is the recommended delivery method due to its flexibility, HTML/JS can be used if the web team is unable to work with JSON. As the JSON method allows for greater flexibility, you are responsible for parsing and styling the recommendations within your web environment. Marketing Cloud Einstein Recommendations enable the creation of product or content recommendations for display on your website. The Einstein Recommendation Engine necessitates a minimum of three active items in your product catalog. Incorporate any catalog field into the web recommendation call, emphasizing a clear understanding of the data driving recommendations during catalog setup. A unique web recommendation call is generated for each page type, with Home, Product, Category, Cart, and Conversion pages recommended as a best practice. However, there is no restriction on the number of pages that can be configured in the UI. Page templates are utilized by Einstein Recommendations, treating a Product Page as a template for building personalized recommendations specific to a product page. Different types of page templates may have distinct scenarios and contexts. For instance, recommendations on a product page may be based on the viewed product, adding context. Conversely, homepage recommendations rely on overall user affinity, lacking specific context. Integrate the Einstein Web Recommendations code into the designated page’s code, incorporating both the JavaScript for the recommendation call and the HTML recommendation zone placeholder provided. Select and configure the content to be included in your web recommendations: 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 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 Guide to Creating a Working Sales Plan Creating a sales plan is a pivotal step in reaching your revenue objectives. To ensure its longevity and adaptability to Read more Salesforce Artificial Intelligence Is artificial intelligence integrated into Salesforce? Salesforce Einstein stands as an intelligent layer embedded within the Lightning Platform, bringing robust Read more

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May 16, 2024in Generative AI, Salesforce Einstein

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