Podcasts about salesforce einstein

In this episode of OnBase, host Chris Moody sits down with Craig Chiofalo to explore what it truly takes to build and lead a world-class support engineering organization. Craig pulls back the curtain on the operational strategies and tech stack powering Demandbase's award-winning team—including how tools like Salesforce Einstein and SupportLogic are transforming their approach to proactive support. He also shares lessons on hiring for excellence, scaling impact without ballooning headcount, and why deep, daily collaboration across product, engineering, and customer success is the cornerstone of lasting success.Key takeawaysRight Team, Right Tech: Hiring the right talent, enabling them with strong onboarding and internal tools, and layering in AI-driven technologies can drive exponential impact without scaling the team linearly.Cross-Functional Collaboration Is Everything: Craig attributes much of the team's success to deep integration with product, engineering, and customer success—teams that work together daily to elevate the customer experience.Award-Winning Process Maturity: From rewritten job descriptions to internal training certifications and advanced sentiment monitoring, Craig's team has refined its approach year after year to earn industry recognition.Operationalized AI: AI tools like SupportLogic and Salesforce Einstein are leveraged not just for efficiency, but for better sentiment analysis, proactive support, and smarter data insights.Measure What Matters: In addition to SLAs, Craig's team emphasizes customer satisfaction and effort scores—tracking detailed metrics while staying focused on proactive issue resolution.QuotesOn Team Excellence“This team is phenomenal—not just individually, but in how they collaborate. That synergy is the catalyst behind everything we've achieved.”On Leveraging AI Thoughtfully“AI should be seen as an assistant. It's like a dishwasher—you still load it and unload it, but it saves time and effort on repetitive tasks.”(04:00): How Craig rewrote job descriptions and created testing processes to hire and retain top-tier talent.(09:00): A deep dive into Salesforce Service Cloud, SupportLogic, and the internal troubleshooting app that dramatically reduces time to resolution.(14:00): How the team uses data and proactive alerts to prevent fires before they happen.(18:00): Craig's thoughtful breakdown of AI as a productivity enhancer, not a replacement.Tech RecommendationsSalesforce Service Cloud + Einstein: A central support platform now enhanced with AI capabilities for smarter case handling.SupportLogic: Real-time sentiment analysis and escalation prediction across customer interactions.Resource RecommendationsNewsletter:MIT Technology Review – AI-focused and practicalHarvard Business Review – Daily updates on leadership and strategyMcKinsey – Insightful newsletters with AI-related contentShout-outsUmberto Milletti, Chief R&D Officer at DemandbaseAngelle Stromeyer, RVP Customer Success at DemandbaseErika Setla, Sr. Director, CX Strategy & Ops at DemandbaseAbout the GuestCraig Chiofalo is a customer-focused leader with over 20 years of experience directing customer support, service, and success teams across SMB to enterprise clients. Currently Vice President of Support Engineering at Demandbase, Craig leads a Stevie Award–winning team recognized for delivering outstanding customer service. He brings a proven track record of building high-performing, collaborative teams that exceed goals, with a leadership style rooted in fairness, energy, and a deep passion for technology.Craig has held key roles at IBM, Silverpop, CallRail, Calendly, and Salsify, often joining during critical growth phases to scale operations, implement smart automation, and drive cross-functional alignment. His expertise spans platforms like Salesforce, Zendesk, Jira, Confluence, and SQL—always with a hands-on, data-informed approach to delivering exceptional customer outcomes.

In this episode of DevOps Diaries, Jack McCurdy sits down with Dave Carroll, a veteran in the Salesforce ecosystem. They discuss Dave's journey from being a Salesforce ISV partner to a key player at Salesforce for 21 years. Dave's mission has been to help develop the tools and practices that empower Salesforce developers to be successful, and has graciously stepped out of retirement briefly to appear on DevOps Diaries.Jack and Dave's conversation covers the evolution of Salesforce, the importance of customization and integrated solutions, as well as the challenges faced by developers across the development lifecycle.Dave shares insights on what it takes to build a successful developer evangelism team through experimentation, and offers valuable advice for aspiring developers looking to navigate the Salesforce ecosystem successfully.Dave Carroll was a Senior Director at Salesforce, managing product development for Salesforce DX, Salesforce Einstein, and was the founding member of the Salesforce developer relations programme.Learn more:How to pick the right Salesforce DevOps solution for your needsWhat is Platform Engineering and how does it impact Salesforce DevOps? Salesforce DevOps for Enterprise customersImprove the quality, performance, and security of your Apex codeAbout DevOps Diaries: Salesforce DevOps Advocate Jack McCurdy chats to members of the Salesforce community about their experience in the Salesforce ecosystem. Expect to hear and learn from inspirational stories of personal growth and business success, whilst discovering all the trials, tribulations, and joy that comes with delivering Salesforce for companies of all shapes and sizes. New episodes bi-weekly on YouTube as well as on your preferred podcast platform.Podcast produced and sponsored by Gearset. Learn more about Gearset.Subscribe to Gearset's YouTube channelLinkedIn: https://www.linkedin.com/company/gearsetX/Twitter: https://x.com/GearsetHQFacebook: https://www.facebook.com/gearsethqAbout Gearset: Gearset is the leading Salesforce DevOps platform, with powerful solutions for metadata and CPQ deployments, CI/CD, automated testing, sandbox seeding and backups. It helps Salesforce teams apply DevOps best practices to their development and release process, so they can rapidly and securely deliver higher-quality projects. Get full access to all of Gearset's features for free with a 30-day trial.Chapters:00:00 Introduction to Dave Carroll and His Journey02:54 The Evolution of Salesforce and Developer Tools05:52 Customizability and Integration in Salesforce08:59 Developing for the AppExchange Platform11:51 Salesforce DX and Developer Tooling17:52 Challenges in Developer Experience and Testing23:48 The Role of AI and Machine Learning in Salesforce29:

Daryl Martis of Salesforce and Rashna Chadha of AWS share how Amazon Bedrock integrates with Salesforce to enhance AI applications, highlighting the partnership's strategic benefits, AI model customization, and secure deployment options.Topics Include:Introduction to Amazon Bedrock and Salesforce partnership.Overview of Amazon Bedrock as an API-based generative AI service.The strategic collaboration between AWS and Salesforce.Salesforce Data Cloud and its integration with Amazon Bedrock.Overview of Salesforce Einstein and its use of Amazon SageMaker.Recent AI launches between Salesforce and AWS, including Slack AI and MuleSoft.Use cases of AI services like Amazon Textract within Salesforce.Bringing Your Own Large Language Model (BYO LLM) with Bedrock.Foundation models offered by Amazon Bedrock (Anthropic, Cohere, Llama).Overview of security, privacy, and compliance in Bedrock AI services.Salesforce Data Cloud's unified customer data and real-time AI capabilities.Bedrock's support for custom AI model evaluation and metrics.Consumption models in Bedrock: on-demand vs. provision throughput.Bedrock's agent capabilities for real-world applications like scheduling.Demo of using Amazon Bedrock models within Salesforce.Participants:Daryl Martis – Director of Product Management, Einstein AI - SalesforceRashna Chadha – AI/ML Specialist – Principal Solution Architect – Amazon Web ServicesSee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

What if your customer data could be the key to transforming your business? Join Jeannie Walters as we explore ways to turn overwhelming data into actionable insights. This episode starts with examining your approach to customer data, setting clear objectives like improving customer retention to make your data analysis meaningful and targeted. We tackle the challenge of data silos by exploring Customer Data Platforms (CDPs) such as Telium and Adobe Experience Platform to centralize your data. With your data in one place, discover how AI and machine learning tools like IBM Watson and Salesforce Einstein can reveal patterns and insights that drive business success.But that's not all—this episode is packed with resources to propel your customer experience strategy to new heights. Tune in and redefine your customer experience strategy today!Resources Mentioned:Experience Investigators Learning Center -- experienceinvestigators.comLearn more about CXI Ground School™ -- cxigroundschool.comWatch the video version of this episode on YouTube -- youtube.com/@jeanniewaltersWant to ask a question? Visit askjeannie.vip to leave Jeannie a voicemail! (And don't forget to follow Jeannie on LinkedIn! www.linkedin.com/in/jeanniewalters/)

In this episode, we discuss the strategic move by Salesforce Einstein Studio to open its doors to user-provided AI models, enabling a new level of customization. Delve into the implications and opportunities that arise as businesses now have the ability to bring their own AI into the Salesforce ecosystem. Invest in AI Box: ⁠https://Republic.com/ai-box⁠ Get on the AI Box Waitlist: ⁠https://AIBox.ai/⁠ ⁠AI Facebook Community Learn About ChatGPT Learn About AI at Tesla

Immerse yourself in the tech evolution as Salesforce Einstein Studio adapts, now allowing users to bring their own AI models. Join this episode for a deep dive into the evolution of AI integration, challenges faced, and the potential impact on the broader landscape of artificial intelligence in business solutions.

Venture into the tech frontier as Salesforce Einstein Studio breaks ground, now supporting your own AI model. Join this episode to explore the frontiers of technology, gain insights into challenges faced, and discuss the potential advancements in user-centric AI integration within Salesforce.

Envision the future of AI integration as Salesforce Einstein Studio transforms, allowing users to bring their own AI models. Join this episode for insights into the strategic considerations, challenges overcome, and the reshaping of AI adoption within the Salesforce ecosystem with this user-centric feature.

Witness a breakthrough in custom AI integration as Salesforce Einstein Studio opens its doors, allowing users to bring their own AI models. Join this episode for an in-depth exploration of the technological advancements, user-centric capabilities, and the transformative impact on AI adoption within the Salesforce ecosystem.

We are LIVE with Episode 15 of the Hot Desk Podcast with Patrick Moorhead and Melody Brue! This week, Box acquires Crooze, Ceridian snags eloomi, Salesforce gets smart at NRF with EinsteinAI in Marketing Cloud, and in Hot or Not: Kyte Baby RTO.   Box Acquires Crooze https://blog.box.com/box-acquires-crooze-transform-enterprise-content-management https://www.linkedin.com/posts/melodybrue_ecm-acquisition-modernwork-activity-7155972822362726401--bBR?utm_source=share&utm_medium=member_desktop   Ceridian to Acquire eloomi  https://www.ceridian.com/company/newsroom/2023/ceridian-to-acquire-eloomi-a-market-leading-learning-and-development-platform   Salesforce Einstein 1 in Marketing Cloud https://finance.yahoo.com/news/salesforce-crm-unveils-genai-powered-131000580.html   Hot or Not: Kyte Baby RTO https://www.hr-brew.com/stories/2024/01/24/kyte-baby-remote-work-mishap https://kytebaby.com/   Disclaimer: This show is for information and entertainment purposes only. While we will discuss publicly traded companies on this show. The contents of this show should not be taken as investment advice.

In this episode, we dissect the transformative announcement from Salesforce Einstein Studio, showcasing how users can elevate their AI capabilities by integrating their own models into the platform. Invest in AI Box: ⁠https://Republic.com/ai-box⁠ Get on the AI Box Waitlist: ⁠https://AIBox.ai/⁠ ⁠AI Facebook Community Learn About ChatGPT Learn About AI at Tesla

Delve into the recent development at Salesforce Einstein Studio, enabling the integration of external AI models. Join me as I discuss the practical applications, benefits, and the newfound flexibility for tailored AI solutions within Salesforce. Invest in AI Box: https://Republic.com/ai-box Get on the AI Box Waitlist: ⁠⁠https://AIBox.ai/⁠⁠ AI Facebook Community Learn more about AI in Video Learn more about Open AI

In this episode, discover how Salesforce Einstein Studio empowers businesses to take AI customization to a whole new level. With the ability to bring your own AI models, companies can tailor their AI solutions precisely to their unique needs. Join us as we delve into the game-changing possibilities that this new feature offers for businesses and AI enthusiasts. Get on the AI Box Waitlist: https://AIBox.ai/Join our ChatGPT Community: ⁠https://www.facebook.com/groups/739308654562189/⁠Follow me on Twitter: ⁠https://twitter.com/jaeden_ai⁠

Discover how Salesforce's Einstein Studio is giving businesses the power to customize AI solutions with their very own models. Join us as we delve into this exciting development, showcasing how it empowers organizations to harness AI's potential like never before. Dive into the future of AI customization in this engaging episode! Get on the AI Box Waitlist: https://AIBox.ai/Join our ChatGPT Community: ⁠https://www.facebook.com/groups/739308654562189/⁠Follow me on Twitter: ⁠https://twitter.com/jaeden_ai⁠

Discover the latest developments as Salesforce Einstein Studio opens its doors to your AI innovations. In this episode, we delve into how you can now seamlessly integrate your own AI models with Salesforce's cutting-edge platform, revolutionizing the way businesses leverage AI for success. Join us for insights on the future of AI in customer relationship management. Get on the AI Box Waitlist: https://AIBox.ai/Join our ChatGPT Community: ⁠https://www.facebook.com/groups/739308654562189/⁠Follow me on Twitter: ⁠https://twitter.com/jaeden_ai⁠

UiPath's recent earnings beat and raise provides some evidence that thus far, Gen AI has not been diluitive for the company. As an early leader that is transforming beyond RPA toward end-to-end enterprise automation, UiPath, like all automation providers, has always faced adoption headwinds beyond isolated deployments. In this sense, Gen AI should bolster adoption and be a positive force. The flip side is that widely available tools like chatbots and generalized foundation models could eat away at the low end of the automation TAM, highlighting the urgency for companies like UiPath to move up market and accelerate innovation that brings differentiation from commoditized tools; and, importantly, create distance from embedded AI within mainstream enterprise SaaS platforms like Slack GPT and Salesforce Einstein. In this Breaking Analysis we briefly review the recent earnings print from UiPath. We'll look at ETR survey data that shows Microsoft Power Automate's impact on the automation market and how it is forcing UiPath to target larger accounts with a more functional product set. As well we'll look at the impact that AI is having in these larger accounts and test UiPath management assertions that Gen AI will be a tailwind for the company. Q2 ‘24 $PATH Earnings Transcripthttps://seekingalpha.com/article/4633537-uipath-inc-path-q2-2024-earnings-call-transcript?feed_item_type=news&utm_medium=referral&utm_source=msn.comGartner MQ for Robotic Process Automation https://www.gartner.com/doc/reprints?id=1-2EDXTGOY&ct=230705&st=sbBarron's article frames the quarter and the AI debatehttps://www.barrons.com/articles/uipath-stock-earnings-artificial-intelligence-cfde9bcbAutomation Anywhere survey on GenAI adoption in automation use caseshttps://www.prnewswire.com/news-releases/generative-ai-emerges-as-essential-tool-for-successful-process-automation-automation-anywhere-survey-finds-301895896.htmlMotley Fool Bull/Bear case for UiPathhttps://www.fool.com/investing/2023/09/07/uipath-stock-bear-vs-bull/Power Laws have more power than you thinkhttps://every.to/p/power-laws-have-more-power-than-you-think

In this informative episode, we delve into the significant update in Salesforce's Einstein Studio, highlighting its new capability to integrate custom models, starting with Amazon SageMaker. Learn from experts about the nuances of this integration, potential use-cases, and how it might revolutionize your CRM strategies by leveraging AI and machine learning. Get on the AI Box Waitlist: ⁠https://AIBox.ai/⁠ Investor Contact Email: jaeden@aibox.ai Facebook Community: ⁠⁠https://www.facebook.com/groups/739308654562189/⁠⁠ Discord Community: ⁠https://aibox.ai/discord⁠ Download Selfpause: ⁠https://selfpause.com/Podcast⁠ Follow me on Twitter... er... X.com: ⁠https://twitter.com/jaeden_ai⁠

The Marketing AI Show is back! The smart CRM market is evolving…and so are marketers and businesses with the help of AI.  First comes ChatSpot, then comes Salesforce Einstein GPT Coming on the heels of HubSpot's ChatSpot announcement, Salesforce just announced Einstein GPT, a generative AI tool for its market-leading CRM. The tool, which is currently in closed pilot, creates content across marketing, sales, and service use cases. Salesforce's communications say, “Einstein GPT will infuse Salesforce's proprietary AI models with generative AI technology from an ecosystem of partners and real-time data from the Salesforce Data Cloud, which ingests, harmonizes, and unifies all of a company's customer data.” They say Einstein GPT can generate personalized emails, generate specific responses for customer service teams, generate targeted content, and auto-generate code for developers. In the same breath, the company also announced a $250 million Generative AI fund through its venture arm.  The value (or lack thereof) gained by AI is dependent on three factors.  Paul recently published a post on an AI topic framing his idea of  “the law of uneven AI distribution.” In it, he wrote: “The Law: The value you gain from AI, and how quickly and consistently that value is realized, is directly proportional to your understanding of, access to, and acceptance of the technology.” This uneven distribution will create dramatic differences in people's experiences with and perceptions of AI. And it's all dependent on three factors: how well you understand AI, the level of access you have to AI, and how much you accept the radical changes that AI will bring about in business and society.  Do we need to fill the time saved by AI with more…work?  When we talk about AI, we often hear that the wondrous productivity gains produced by AI technology will give us back more time, in turn making our lives less busy and more fulfilling. And these productivity gains are valuable. Venture fund ARK Invest predicts that we could boost the productivity of the average knowledge worker by 140% with AI, which would create $56 trillion in value globally. But a new article from the Centre for International Governance Innovation challenges the idea that AI will liberate our time and goes so far as to call the AI productivity narrative “a lie.” However, history has shown that efficiencies often heighten expectations and standards. How can we as marketers, business leaders, and humans, ensure we aren't exacerbating Parkinson's law by adding to the idea that “work expands so as to fill the time available for its completion?” How can we invest that time in things we want to do? This is a topic we all need to listen to!

Hello, welcome back to the Recruitment Hackers podcast. I'm your host, Max Armbruster. And today, inviting to the show for the first time, Mr Martyn Redstone, who is an Uber geek, and an analyst of the TA tech world and who has been working in the world of recruitment chatbots and conversational AI, for as long as the industry is, which is only about five or six years but has been consistent in his interest of finding ways to connect with candidates faster through the use of technology. And so today's discussion will be about that exactly; like how - what's the next step for talent acquisition in terms of treating candidates, like customers and getting a little bit closer to them? And what can we learn from the world of consumer marketing? So that we can - because usually, recruitment is a little bit behind consumer marketing. Recruitment marketing is usually a few years behind consumer marketing. So what can we learn from the leading technologies in that space and the best practices in consumer marketing? Notably, because Martyn has recently spent some time working with Hootsuite, which is a company which specializes in omnichannel marketing and delivering messages to different channels like Twitter, Instagram, Facebook, etc. So there's a - yeah, there's probably some good parallels that can be drawn from there, or that's what we're hoping for. And finally, Martyn, for your introduction. Martyn is also the founder of Bot Jobs, which is a job board for people who little bit - who are in love with bots, and who prefer to talk to bots than to talk to humans. So they can go to that job board and they can find other - they can find opportunities for people like them. Is that a fair summary? Martyn?I think so. I think so. Yeah. And, just for the benefit of everyone else, I did give Max permission to call me an Uber geek. So it's not a derogatory term. Very proud of that, actually. But yeah, no, thanks for the introduction. Yeah. So, Bot Jobs, just to clarify is a job board for conversational AI professionals. So everything from Conversation Designers through to Engineers, Software Developers, Marketers, Salespeople, anything to do with that conversational AI ecosystem. It's a bit of fun, but it's enjoyable. Great to see the trends and keep my toes dipped into the world of recruitment as well. So when we look at the kind of conversational AI world, hiring, still going like the clappers. In the - on the tech vendor side of things, we're still seeing hiring in kind of the smaller and medium-sized tech businesses, the ones that have already gone through, they're kind of their seeds, their seed rounds, their series A's, you know, they're still got cash, they're still growing. And some of them are doing exceptionally well from a growth perspective. And they're still hiring like the clappers. What we're also seeing, quite interestingly is large corporates that are now realizing that conversational AI has to be part of their strategy, their business strategy, and so they're starting to hire internal conversational AI teams to run that customer experience, customer context strategy. So that's very, very interesting. But to go back on your, on your point about job creators and job destroyers, I think that's a, I think that's something that I've been dealing with for the last five or six years that you've mentioned, I've been in this world where people say, oh, you know, chatbots, you know, and automation, it's just, it's just going to replace people, it's just going to take over people's jobs. And that's what you're out for, you're out to kind of replace recruiters with bots. Now, interestingly, over the last five or six years, I've never actually really seen that. I've never seen - And we've seen examples where chatbots in the retail world or in the recruitment world have automated up to like 85% of all conversations that happen. And yet, we haven't seen 85% of recruiters or 85% of customer service people being laid off because of that. And a great example is a global sports retailer who were able to literally turn off their customer service telephones because their conversational AI solution was so strong, they were able to turn off all their phone lines and deal with every single inbound inquiry. Over - actually, Facebook Messenger was where most of their conversations happened. But actually, what that meant was they realigned their customer service team into providing higher - providing service into higher value conversation. So conversations where they can upsell where somebody is then transferred to a person to say, you know, I - wondering if this is in stock, or something that the conversational AI couldn't cope with, where they had the ability to actually increase the revenue coming into the business through customer service. So a lot of businesses now are seeing customer service as a revenue centre, rather than a cost centre, because they're able to actually concentrate now on higher-value conversations rather than the just - the mundane stuff that can be automated. I see that happening in talent acquisition as well, where we're going to find that we're when we start taking away some of the more mundane repetitive stuff from recruiters that they're able to become more high-value partners to the business and to the hiring managers and to their candidates as well. Which I think is going to happen. I don't see it as a race to replace people.Yeah, yeah I mean, I would say that there is some truth to automation, killing some jobs. But of course, recruiters have the EQ and the experience who reinvent themselves and be relevant in a more automated world, because certain things will not be automated. So yeah, that's the projected outcome for us is that they'll still be there. Recruiters will still be there to sell the job. They'll still be there to get people excited. They may not be needed for the repetitive you know, data collection piece of it. You mentioned the - some layoffs at Alexa and Salesforce Einstein products, but that generally, bots are doing well. The corporate world is buying more. I'm, wondering about, you know, the Hootsuite experience, if that's not too confidential, if you can share - what's been the adoption of Heyday, you said it was their conversational product and what - why did they decide to step you know, or slow down there?Yeah, that's a good question. Obviously, if you appreciate some things, I can talk about something. Yeah. But yeah, ultimately, Heyday was focused on e-commerce and retailers. So it was a very niche product. But the uptake was always great, you know, every single retailer, especially during the pandemic, what what was, what was obvious was that every brick and mortar retailer that had shops couldn't have their shops anymore because of lockdowns and things like that. So every retailer became an E-commerce business. And so they need to do more with less which we know that everyone tries to do in times of economic shock. So obviously a conversational AI tool that's focused on e-commerce and can do things like not only, not only answering FAQs, all those kinds of standard things, but also being able to sell things from within chat, so adding things to your basket doing checkouts, but also keeping people updated on their order status, as you know, I think if you speak to most retailers, is 70 to 80% of all of their customer service inquiries are going to be where's my order? So being able to just do it, you can automate that is a very, very powerful - creates a very powerful business case. So absolutely, you know, the adoption was there. The challenge that, and I think I can talk generically about most tech businesses that have been going through these reductions and transformations is that most tech businesses didn't see - didn't predict the change in the market would happen post-pandemic. And I think that a lot of businesses have been caught by that.  Yeah, because they had a crazy, they had a crazy boom. And it's slowed down because, well, consumer spending slowed down, everything slowed down a little bit. So yeah, they couldn't repeat 2021. Now, so it's more contextual than then technology. But the technology is still valid. And the most popular question for the bots was where's my order? So what can we learn from that? On the recruitment side? How do we apply this experience? From E-commerce to recruitment? What's the equivalent of where's my order?Do you know what? I think that I was only at HootSuite for a short time. And I've been in the recruitment industry for 17 years, and I only had a four-month break of going into kind of the retail/e-commerce sector. But the amount that I was able to understand and pick up around the expectation of a consumer was quite interesting. So not only the whole “where's my order thing”, but also channels as well. So I think we're, I think as an industry, we've always been quite - I say this in the nicest possible way - arrogant around us knowing what our candidates expect from us. And I think that we're the ones that tell candidates what they need to expect from us rather than the other way around. So, you know, I mentioned Facebook Messenger, earlier with the global sports brand, but you know, the multitude of channels that candidates or consumers want to interact with businesses on whether it's WhatsApp, whether it's Facebook Messenger, whether it's Twitter, Instagram, Tik Tok, you know, there's a massive boom of Commerce on Tik Tok, as well. And that just shows the change in generations and the changing consumer behaviour, but I think it's important to make sure that you give the person that you're engaging with as a business, that agency to say, you can talk to us on any channel that you'd like to at any time of the day or night. And that's where that kind of conversational automation comes into it. So, so the first thing is the channels and thinking about where your people are, that you're interacting with, what's the door to your business. What's your - What channel are they coming in on; where are they? And that changes all over the world, as you know, you know, wherever you are in the world, people's behaviour in terms of the technology they use to communicate with changes. But the other interest is, like you said, the whole kind of where's my order thing? You know, it. And I think if we'd have gone into a business and said, right, you know, we're automating your FAQs, we're automating “do you have this, these pair of trousers in white and a size, in a medium size in stock in my local store”, would it have gone: “this is exactly what you want”?. Because you know, this is where we think everybody's going. But actually, when you talk to the business and say, Okay, tell us, your 80% of all of your, of all of your conversations coming into your customer service team. Tell us what those 80% are. And, you know, the massive chunk of that is where's my order? And then there's a little bit of what's your returns policy? Or what's your opening times on your stores, things like that?Yeah,it's about understanding business. SoI totally know what you mean. And I just want to rephrase it for our listeners. So a lot of time in the Chatbot world. A lot of investments will be spent on the initial engagement, where a candidate would come in and would come in asking questions like, What kind of jobs do you have? What is the right career path for me? And that has attracted investments, as well as marketing pitches, and a lot of companies have been focusing on that. But actually, candidates never really asked for a new place to search jobs because they already have websites and job listings and things like that, what they want is connectivity. They - what they want is also the where's my order afterwards. So if you start your research from the moment that they have placed an order or in Job parlons, they've applied for a job. And then you figure out how to use NLP and conversational AI to take care of them from that moment on, you're gonna get more benefit - a lot more benefit for a lot less investment, basically, did I? Is that a good rephrase? Yeah, absolutely. And I think that, and I really didn't want to mention this today. But I think that's what, that's what I'm excited about with chat GPT, there's not much that I'm actually excited about it with. But what I'm excited about it, what excites me about chat GPT is the realization that people are having, that a conversational tool isn't just transactional. And it can be a true assistant, basically. And that's the long tail kind of plan for most of these assistants that we work with. And I can't really say them out loud for the benefit of everyone's got them on their desks everywhere, not really trigger everybody's technology in the room. But you know, the little pucks that people have on their desks and what have you, you know, the whole point of that is, eventually there'll be a complete conversational assistant. And that's what, that's what people come to expect now from a brand you know, so if you're, if you're doing a, an application via WhatsApp, let's say, just think about how you deal with a WhatsApp message from your friends or from your family, you know, you pick it up, you open WhatsApp, and you send a message and you expect a response at some point, that's the same expectation they have with the brand. So somebody's applying for your job. By WhatsApp, they've got that message still on there on their phone, they're going to pick it up, and they can message it and say, hey, just wondering what's going on with my application. That's a natural instinct for somebody nowadays to have. So thinking of it as a conversational tool as a conversational assistant, to your application process, and your interaction with business, not just a transactional, “I've uploaded my resume, here's my link to my LinkedIn profile, off you go”. You know, it's, it no longer should be looked at as transactional, it should be looked at as a, as a long term, relationship based conversational journey.I'm thinking we should start as well. Flagging if candidates are using chat TBT to answer interview questions, because we, you know, we asked millions of interview questions every month, and we do evaluate the quality of their answers. And Chad GPT seems like it does a pretty good job. So but there there there are tools now to determine when or whether there's a high likelihood that this was generated by Chat GPT. So if somebody if a candidate did use it, should we eliminate them from consideration or maybe even bump up their application to the top of the pile because, you know, their use of technology?I heard a great analogy this morning about Chat GPT, and it got - and I'll probably get it totally wrong because I'm on the spot here. But, it went something like this, you know, several 1000 years ago, when, when people started building things with wood, you know, they probably had a rudimentary nail that they were slamming him with a rock or something. And not once, yeah. And finally, an apprentice built something called a hammer and start hitting a nail in with a hammer. Not once, did anyone say how they use that hammer to do something more efficiently? They thought, What a great idea. It's giving you a helping hand to speed up your, your process to get things done better. And so do we now think that we should be chastising people for Chat GPT because it's merely a tool to do something more efficiently? So a lot of people now have, you know, challenges, you know, not even now, a lot of people have challenges in how to answer something. And so the whole point of chat GPT is to give that person a helping hand because a lot of the stuff that spurts out is, is hallucinogenic. But, ultimately, because of the way it works, it can't always give you something that's factual. And I won't bother going into the technicalities behind it. But it won't be ever 100% factual.So it gets its wisdom from the internet. Sowell, it's not even about where it gets, okay, I'm gonna say it. So it's, it's not even about where it gets its wisdom from but the whole point of the GPT model is it's an algorithm for under - for predicting which word comes next in it. A string of text. So, that's the way it works. It's not even just about it goes off into its model, find some information regurgitates it. That's how it learns, it learns on the information, it learns on the patterns of words and all those kinds of things. What it's actually doing is using that learning to understand the subject, but then to predict each word that comes next in the sentence or a string of text. And so that's why it's very, very good at predicting it. But it's not always going to be 100% correct. And that's why it becomes quite, I call it hallucinogenic. Because it feels like sometimes it's hallucinating. I've run various tests on it, and various experiments, and it's it, you can't rely on it to be factual. But ultimately, what you can rely on it to do is to string those words together. And so it's a great place to start. If you're struggling on how to start off your response to an interview question, start off your blog, start off your LinkedIn posts, all those kinds of things, because you should be using it to generate ideas and easy-to-generate structure, then go in and make it your own. So I go back to my original point, do we chastise people for using chat GPT to give them a helping hand in doing their job properly, or applying for a job? Or do we see it as a bad thing? I think - I'm still open to ideas on this. But I like to put it out there as a thought.Yeah, yeah. Well, I mean, you know, Oscar Pistorius was not allowed to run that race with his enhanced leg. I'm not sure I'm pronouncing his name correctly, and candidates are being evaluated on their communication skills and written ability. You know, of course, it feels like, it feels like they're being they're cheating, or, you know, it's cheating, but I get your point. It would be a better employer, who would ask the candidates, you know, please, please ask an intelligent prompt to chat GPT to solve this problem.And ultimately, as professionals in the world of talent acquisition, we and kind of people-related stuff, we need to understand that the world is changing, and it's changing very, very rapidly. You know, two years ago, you would never have heard of a job title called a prompt engineer. And yeah, I know, you know, I personally know Prompt Engineers. Exactly.Do they have prompt engineers on your job board already?Not yet. No. Coming soon, there is talk about kind of adding some generative AI stuff onto there in terms of jobs, but I'm very focused on conversational AI, which is a slightly different kind of realm of artificial intelligence. But, you know, talk about conversational AI. You know, 5-6-7 years ago, nobody was talking about conversation designers as a job. And yet, you know, that's one of the hottest jobs in the world right now. Is a conversation designer, and people, you know, 18 months, two years ago, three years ago, when I talked about the fact that I trained as a conversation designer, people were just laughing at me thinking, you're off your rocker, you're on a different planet. What the hell is a conversation designer?I used to make that joke to my team because we had our conversation in 2016 by 2018, you know, they were getting so many looks on LinkedIn, you know, who they were, you know, it was impossible to keep them basically. I should have kept their job titles like Technical Support Engineer.Yeah. But it just goes to show; so in 5-10 years time, are we expecting copywriters? Are we expecting marketers to come up with their own original content and their own original ideas? Or are we expecting them to utilize the tools that are available to them to generate ideas and allow them then to take those and move them forward into something amazing?Yeah, I think that's a rhetorical question. So I'm gonna ask you, what is my final question on everyone of -for every one of my guests come to the podcast, which is to talk about a recruitment mistake that you made in the past. And I don't know if you've hired anyone recently, but it can be, you know, recent or the long, long ago past may be a memory that you've managed to silence because make a wrong hire. But Trent, if somebody's listening right now, maybe they can avoid to make a terrible mistake based on your experience. So does that experience you have one in mind that comes to mind - a miss hire you made?That's a really good question. I would say quite the opposite. I know this sounds terrible.But I think one of the biggest mistakes So I probably made in my, in my career when it came to hiring and people was I once took over a team. And actually, I was actually I was promoted from within that team to, to head it up, which is always a difficult situation anyway, because you're when you're young and you're full of energy, and you're quite new into the world of work and you think, great, this is my first opportunity in a kind of a leadership position, you don't really understand some of the complexities of people and what have you. And so, I think that one of my, one of my biggest mistakes, I don't think was about hiring people. I think it sounds terrible, what to say out loud about people keeping people Yeah. And so, you know, the challenge I had was, because I spent some time working as part of that team. I knew that there was some of them that weren't, they weren't up to the job and weren't able to perform as well as other people. And I, in the most humanitarian way I should have, should have let them go as quick as I could do. But because of that relationship that you have with those people, and because you want to, you don't want to come across as like the ogre that's taken over and chopped everyone away. You keep people on for the sake of keeping people on and sometimes you have to make a brave decision, that that has to be made. And that's part of having a leadership responsibility that sometimes you have to make decisions that aren't comfortable for you or for other people.Grow up people, you know, if you're a manager, you're gonna have to, you're gonna have to hire sometimes, and sometimes, you know, recruiting is of course, fraught with dangers, and you can make a lot of mistakes, but it's better hiring somebody and risking hiring the right person rather than being 100% sure you're keeping the wrong one?Absolutely. Absolutely. You know, and that was a long time ago, I had hair and I didn't have any grey in my beard. So yeah, so that was a long time ago. And I've learned a lot since then. But I think if I look back on my career, that was probably one of my first kind of major learning curves was kind of my first real entrance into the world of leadership and management.Max  27:25  It's such a common mistake that people make to delay hiring because they're emotionally invested with an underperformer. And so yeah, sometimes recruiting is exactly what the doctor ordered. Even if you do make mistakes. So takes take risks to take bold risks, especially in this market. Absolutely, totally agree.There's a lot of great talent out there and go to Bot Jobs.Absolutely. For any conversational AI people that you want to hire, Bot-jobs.com Bot hyphen jobs.com.Great. How else can people get a hold of you, Martyn?LinkedIn is always the easiest way. I'm on that thing. 24/7 So so if you want to contact me, it's linkedin.com/in/lastname is Redstone just the way like it's pronouncedspelt like it's pronounced yet. AndLinkedIn, read Martyn's. LinkedIn feed is pretty geeky indeed. So you'reAbsolutely if you want to be immersed into my world of conversational AI and other lovely things then, then connect with me. And yeah, that's the best place to get hold of me.Awesome. Thanks. Thanks for coming on.Thanks for inviting me, Max. Been pleasure.That was Martyn Redstone founder of Bot Jobs, who went on to have a conversation with me about how every big brand is continuously investing in conversational AI and making that connection easier for people to get answers to their question on the most pressing question, which in the consumer space, as he said is, "where is my order" in the recruitment space? What is the status of my application? Hope you got something from that conversation. I certainly did. And that you'll follow us and share with friends so that we can grow this podcast.

Meet Jim Sinai, CMO at Vanilla and former marketing leader at Salesforce. During his 8 years at Salesforce, Jim worked on various businesses including Salesforce Einstein, Salesforce Platform, AppExchange, Data.com, and Salesforce Industries. In this episode, Jim shares the lessons he's learned from his biggest projects at Salesforce and how keeping a beginner's mindset has helped him succeed.Quote“If you're not rooted in the concept of a beginner's mind, your projects will fail.”Episode Timestamps:*(1:56) - Ohana Origins: Meet Jim Sinai *(7:29) -  What Does the Ohana mean to Jim?*(11:53) - What's Cooking: Jim's Current Role at Vanilla*(19:45) - Future Forecast: What's in Store for the Salesforce ecosystem?*(19:07) - Advice for Aspiring Marketing Leaders*(22:22) - Lightning Round!SponsorInside the Ohana is brought to you by Qualified.com, the #1 Conversational Marketing platform for companies that use Salesforce and the secret weapon for Demand Gen pros. The world's leading enterprise brands trust Qualified to instantly meet with buyers, right on their website, and maximize sales pipeline. Visit Qualified.com to learn more.LinksConnect with Jim on LinkedInConnect with Dan on LinkedInLearn more about Vanillawww.caspianstudios.com

Former Ubiquiti developer charged with trying to extort employer New Yanluowang ransomware strain could be the next big threat Why you need a smart carbon monoxide detector Zero-trust architecture could increase cybersecurity efficacy by 144% The big business of library E-books John Kucera, SVP of Product Management for Salesforce talks about Einstein Automate and how it helps small businesses and non-profits. Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: John Kucera Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: itpro.tv/enterprise use code ENTERPRISE30 wwt.com/twit plextrac.com/twit

Former Ubiquiti developer charged with trying to extort employer New Yanluowang ransomware strain could be the next big threat Why you need a smart carbon monoxide detector Zero-trust architecture could increase cybersecurity efficacy by 144% The big business of library E-books John Kucera, SVP of Product Management for Salesforce talks about Einstein Automate and how it helps small businesses and non-profits. Hosts: Louis Maresca, Brian Chee, and Curt Franklin Guest: John Kucera Download or subscribe to this show at https://twit.tv/shows/this-week-in-enterprise-tech. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: itpro.tv/enterprise use code ENTERPRISE30 wwt.com/twit plextrac.com/twit

In this podcast, Salesforce's SVP of Product Management and GM of Einstein, Marco Casalaina discusses how AI is revolutionizing the way businesses interact with their data. Casalaina talks about major advances in machine learning that can now do some work for us more effectively than humans ever could before. One example is Einstein Lead Scoring. The Einstein AI platform creates a model for each lead in Salesforce, to help organizations prioritize their prospects based on data that's unique to them.

Einstein Activity Capture is a great solution for Salesforce activity tracking. Einstein Activity Capture for Salesforce pulls in calendar events and emails and then identifies all the information then matches the information to already existing Salesforce Accounts and Contacts. Visit Us:- https://www.salesdirector.ai/blog/2020/05/06/einstein-activity-capture-and-the-biggest-problems/

เป้าหมายของ Salesforce Einstein คือการให้ฝ่ายขายและฝ่ายการตลาดมีมุมมองที่ครอบคลุมและเป็นปัจจุบันมากขึ้นเกี่ยวกับลูกค้าและแนวโน้มการขายสินค้า ด้วยเทคโนโลยี Machine Learning และ Deep Learning ข้อมูลเชิงลึกของลูกค้าที่ได้จากการรวมระบบของ Einstein สามารถช่วยบริษัทในเชิงรุก หลีกเลี่ยงปัญหาในการบริการลูกค้า และยังสามารถช่วยปรับปรุงการบริการ ด้วยการช่วยคาดการณ์ว่าผู้มีโอกาสเป็นลูกค้าอยู่ในวงจรการขายและช่องทางการสื่อสารใดที่พวกเขาจะต้องตอบสนอง เลือกฟังกันได้เลยนะครับ อย่าลืมกด Follow ติดตาม PodCast ช่อง Geek Forever's Podcast ของผมกันด้วยนะครับ ========================= ร่วมสนับสนุน ด.ดล Blog และ Geek Forever Podcast เพื่อให้เรามีกำลังในการผลิต Content ดี ๆ ให้กับท่าน https://www.tharadhol.com/become-a-supporter/ ——————————————– ติดตาม ด.ดล Blog ผ่าน Line OA เพียงคลิก : https://lin.ee/aMEkyNA ——————————————– Geek Forever Club พื้นที่ของการแลกเปลี่ยนข้อมูลข่าวสาร ความรู้ ด้านธุรกิจ เทคโนโลยีและวิทยาศาสตร์ ใหม่ ๆ ที่น่าสนใจ https://www.facebook.com/groups/geek.forever.club/ ========================= ช่องทางติดตาม ด.ดล Blog เพิ่มเติมได้ที่ Fanpage : www.facebook.com/tharadhol.blog Blockdit : www.blockdit.com/tharadhol.blog Twitter : www.twitter.com/tharadhol Instragram : instragram.com/tharadhol TikTok : tiktok.com/@geek.forever Youtube : www.youtube.com/c/mrtharadhol Linkedin : www.linkedin.com/in/tharadhol Website : www.tharadhol.com

Einstein activity capture is a great step into bringing salesrep activity data (email and calendar events) into salesforce. By default, Einstein activity capture pulls in emails and calendar events and associates them with existing salesforce contacts and accounts. Note, einstein activity capture does not capture new contacts. Visit Us:- https://www.salesdirector.ai/blog/2019/11/27/the-biggest-issue-with-einstein-activity-capture/

This episode features an interview with Jim Sinai, Senior Vice President of Marketing at Procore Technologies, a global cloud-based construction software company that recently went public at an approximate valuation of $9B. Prior to Procore, Jim held numerous senior leadership roles across 8 years at Salesforce, including leading the launch for major product rollouts of Salesforce Platform and Salesforce Einstein. On this episode, Jim unpacks the intersection between product marketing and demand gen, the hardest challenge facing modern marketers, the future of webinars, and much more.Key TakeawaysEvery product marketer must think like a CMO. Messaging is important, but messaging for an entire audience is more important.Whenever you have a disagreement, the answer is not going to be found inside the four walls of the building, it's outside with the customer.If you're a CMO and you're not willing to learn how the demand gen systems work, you're not going to be CMO for very long.Quotes“The best demand gen leaders out there can do product marketing. I've seen them do product marketing, and they all have the same attributes in common, which are stakeholder management and alignment. At the end of the day, what makes for great campaigns and great demand gen is when you have the sales team and the marketing team focusing on trying to say the right message to the right people.” “All good campaigns are really just about trying to get eyeballs back to your website where you're trying to convert things. We have this mantra at Procore in our marketing team that the website is our most important asset. And we put all of our attention to make sure that we have all of our merchandising on the website.” “Just think about how your buyers are humans and they want a really delightful experience on the website. [Maybe] that's integrating a chatbot...One of the things that I think is fantastic is when you don't have to talk to a salesperson to book a meeting with the salesperson. I want to talk to sales and I want to talk to them either now via chat or I want to pick up the phone. Giving the shopper that channel is really important.”“Whenever you have a disagreement, the answer is not inside the four walls of the building, it's out with the customer. So the person who has tested it the most is the person who will likely have the winning argument in a dust-up.” “If you're a CMO and you're not willing to learn how the demand systems work, you're not going to be CMO for long, unless you have a phenomenal demand gen visionary as your right hand..” SponsorDemand Gen Visionaries is brought to you by Qualified.com, the #1 Conversational Marketing platform for companies that use Salesforce and the secret weapon for Demand Gen pros. The world's leading enterprise brands trust Qualified to instantly meet with buyers, right on their website, and maximize sales pipeline. Visit Qualified.com to learn more.LinksWorld of Concrete ConferenceProcore is hiring! Follow Jim on TwitterConnect with Jim on LinkedInFollow Ian on TwitterConnect with Ian on LinkedInwww.caspianstudios.com

Why discuss only one topic when you can discuss three! This week Paul and Rich dig into three unrelated but important topics that they’ve had top of mind. They share musings on going back to the office and break down Natural Language Processing (NLP). Then Paul reveals what he learned from watching a two-hour presentation by Salesforce. Links:  Salesforce Einstein  Postlight - Work

Keep up with the key updates as they happened last week in digital from Adobe, Salesforce Einstein , Amazon Web Services and Appsflyer Amazon S3 Object Lambda - A new capability to manage your data across multiple applications where S3 is the source Adobe Digital Economy Index - Adobe's latest report about customer spends since the pandemic lockdown began in March 2020 and detailed pathway for eCommerce to become at $1 Tn industry by 2022. The New Era in Experience Report : A new research report by Adobe & London school of business categorizes business by Thrivers, Hiders & Survivors, with details on how Thrivers achieve more success from their digital investments, compared to others. Salesforce AI Powered Marketing : Salesforce also announced 2 new capabilities to their Account Based Marketing capabilities within Salesforce Digital 360. The first one, Einstein Key Account Identification uses Artificial Intelligence to surface accounts with highest likelihoods to purchase and provides strong recommendations to market & sell to these accounts. Next up, Accounts as Campaign Members enables Account Based Marketing campaigns personalized for every buyer within top-tier accounts. Best to check out the link in description for more details and demos. Nike Quarterly Digital Earnings - Nike announced generated more than $1 Bn in digital revenue across their businesses in North America

MLOps community meetup #48! Last Wednesday, we talked to Manoj Agarwal, Software Architect at Salesforce. // Abstract: Serving machine learning models is a scalability challenge at many companies. Most applications require a small number of machine learning models (often < 100) to serve predictions. On the other hand, cloud platforms that support model serving, though they support hundreds of thousands of models, provision separate hardware for different customers. Salesforce has a unique challenge that only very few companies deal with; Salesforce needs to run hundreds of thousands of models sharing the underlying infrastructure for multiple tenants for cost-effectiveness. // Takeaways: This talk explains Salesforce hosts hundreds of thousands of models on a multi-tenant infrastructure to support low-latency predictions. // Bio: Manoj Agarwal is a Software Architect in the Einstein Platform team at Salesforce. Salesforce Einstein was released back in 2016, integrated with all the major Salesforce clouds. Fast forward to today and Einstein is delivering 80+ billion predictions across Sales, Service, Marketing & Commerce Clouds per day. // Final thoughts Please feel free to drop some questions you may have beforehand into our slack channel (https://go.mlops.community/slack) Watch some old meetups on our youtube channel: https://www.youtube.com/channel/UCG6qpjVnBTTT8wLGBygANOQ //Relevant Links https://engineering.salesforce.com/flow-scheduling-for-the-einstein-ml-platform-b11ec4f74f97 https://engineering.salesforce.com/ml-lake-building-salesforces-data-platform-for-machine-learning-228c30e21f16 ----------- Connect With Us ✌️------------- Join our Slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Manoj on LinkedIn: https://www.linkedin.com/in/agarwalmk/ Timestamps: [00:00] Happy birthday Manoj! [00:41] Salesforce blog post about Einstein and ML Infrastructure [02:55] Intro to Serving Large Number of Models with Low Latency [03:34] Manoj' background [04:22] Machine Learning Engineering: 99% engineering + 1% machine learning - Alexey Gregorev on Twitter [04:37] Salesforce Einstein [06:42] Machine Learning: Big Picture [07:05] Feature Engineering [07:30] Model Training [08:53] Model Serving Requirements [13:01] Do you standardize on how models are packaged in order to be served and if so, what standards Salesforce require and enforce from model packaging? [14:29] Support Multiple Frameworks [16:16] Is it easy to just throw a software library in there? [27:06] Along with that metadata, can you breakdown how that goes? [28:27] Low Latency [32:30] Model Sharding with Replication [33:58] What would you do to speed up transformation code run before scoring? [35:55] Model Serving Scaling [37:06] Noisy Neighbor: Shuffle Sharding [39:29] If all the Salesforce Models can be categorized into different model type, based on what they provide, what would be some of the big categories be and what's the biggest? [46:27] Retraining of the Model: Does that deal with your team or is that distributed out and your team deals mainly this kind of engineering and then another team deal with more machine learning concepts of it? [50:13] How do you ensure different models created by different teams for data scientists expose the same data in order to be analyzed? [52:08] Are you using Kubernetes or is it another registration engine? [53:03] How is it ensured that different models expose the same information?

Salesforce launched Einstein, its artificial intelligence tool, in 2016. It was memorable because of the marketing materials, featuring a cute cartoon of the world's most misquoted-scientist. It was also memorable because of the unique capabilities Einsten brought to the table. This wasn't some sort of algorithm builder for data scientists. It was a smart assistant woven into the platform. As Salesforce liked to tell me, it "democratized" artificial intelligence. So today we're getting an update on Einstein and how it's grown with the Salesforce ecosystem. Here to tell us about it is Sanjna Parulekar, a Senior Product Marketing Manager, of Salesforce Einstein at Salesforce.

Follow and Connect with me to see #HeadsTalk Podcast Audiograms every Monday on LinkedIn. Episode Title:

In our third episode of Breaking 404, we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for Machine Learning Engineers.About Srivatsan RamanujamSrivatsan Ramanujam is a Director of Software Engineering at Salesforce where he currently leads engineering for machine learning products in Salesforce Einstein. Previously at Salesforce, Srivatsan led the Customer Intelligence data science team, solving problems in customer growth, retention, and platform adoption. Prior to Salesforce he led data science projects for customers in multiple industry verticals at Pivotal (VMWare) and was a lead engineer for NLP products at Sony Mobile and ML products at Sony PlayStation. Srivatsan earned a Masters in Computer Science from the University of Texas at Austin.Follow SrivatsanWebsite: https://vatsan.github.io/Twitter: @being_bayesian

Ayori "Selfpreneur" Selassie was a panelist at the 2018 Blacks in Tech conference. She spoke with such gravitas on the panel that I knew I wanted to interview her. After rebuffing a guidance counselor's advice to study African-American studies instead of computer science, she has embarked on quite a career in the technology space. She has worked in engineering, sales, and marketing, culminating with her current position at Salesforce leading its marketing efforts for Salesforce Einstein. Ayori is also an entrepreneur, with a book coming out in 2020, and her other initiatives, Selfpreneur and Life Model Canvas. Tune in to hear about how her mom was instrumental in her start with coding, what exactly Selfpreneur means (I had no clue), and how she handles nerves before public speaking. Some takeaways from our conversation: 1. Care about what you're talking about when public speaking 2. Speak regularly to get better 3. Gospel music can go a long way... To learn more about Ayori, you can find her at: https://www.selfpreneur.com/ainewbies http://www.lifemodelcanvas.org/ https://www.linkedin.com/in/randomgirl/ https://www.instagram.com/iayori/ https://twitter.com/iAyori https://www.facebook.com/iayori/

Sanjna Parulekar, Salesforce’s Senior Product Marketing Manager for Salesforce Einstein has lived in and around tech her whole life. As both of Sanjna’s parents had careers in tech, Sanjna felt she was destined to follow a similar career path. Fast forward to today when destiny has become reality. Sanjna is currently working with Salesforce Einstein helping to bring to life the influence it has on A.I., CRM, and the world. It comes without surprise that Sanjna is most excited for the future of voice technology, especially considering everything Salesforce is doing with its innovative Einstein Voice Assistant. Sanjna describes the jaw-dropping intricacies of the Einstein Voice Assistant and how it’s going to change the way people do business, view sales, and close deals through the power of A.I. and A.I. personalization. Key Takeaways:   Salesforce Einstein and its influence on CRM and A.I.  Thinking about your customer’s customer  A.I. personalization’s impact   Salesforce and MIT recently teamed up to create a whitepaper exploring what happens when AI meets CRM. Read: AI Meets CRM: An MIT Tech Review Whitepaper This podcast is sponsored by Salesforce. Did you know Salesforce isn't just for Sales? Using Salesforce as an Employee Experience Platform helps make every employee across your organization more productive thanks to a common, mobile-first platform for getting work done faster. Find out more at salesforce.com/EmployeeExperience

When couple of folks from AI and Data Science start discussing about the importance of data analytics and success requirements of ML engine.

Dr. Sarah Aerni is a director of data science at Salesforce Einstein, where she leads teams building AI-powered applications using autoML. Previously, she led teams in healthcare and life sciences at Pivotal building models for customers and cofounded a company offering expert services in informatics to both academia and industry. Sarah holds a PhD in biomedical informatics from Stanford University, where she performed research at the interface of biomedicine and machine learning.

On this special mixdown episode of IT Visionaries we are focusing on artificial intelligence. In the first 65 episodes of IT Visionaries, we’ve had on countless experts who are working with some of the most advanced A.I. technology in the industry, and they spilled all the cool details to us. So on this episode, you’ll hear from Ali Bouhouch of Sephora, who talks about the ways A.I. will continue to enhance customer experience, we’ll listen to Marene Allison of Johnson & Johnson discuss where A.I. is on the maturity curve, and how far it still needs to come to be trusted in certain industries. Eric Tan of Coupa explains how AI and machine learning will better use the mass amounts of data being collected, Julien Sauvage, who works on the Salesforce Einstein team breaks down some A.I. use cases, Vijay Doradla of Sparkcognition reveals the way AI will become part of everyday life, and Andrea Brugger of United Rentals speaks from a sales perspective about the way A.I. is impacting the construction industry. Topics discussed: A.I., machine learning, apps, data IT Visionaries is brought to you by The Lightning Platform by Salesforce. The Lightning Platform is a leading cloud platform that makes building AI-powered apps faster and easier. With Salesforce, now everyone is empowered to build apps for their organization! Learn more at salesforce.com/buildmobileapps. Salesforce and MIT recently teamed up to create a whitepaper exploring what happens when AI meets CRM. Read: AI Meets CRM: An MIT Tech Review Whitepaper

Stop what you're doing. Step back. Take a breath. Surely there's a better way of getting this done. Surely there are new approaches we can take to getting our message heard. Surely there are new technologies that will make our work bigger, faster, stronger, better. Good news - there's all that and more just around the corner. During this podcast, you'll discover:Innovation trends we'll see take off and make a serious impact in 2019.The latest strategic approaches to maximising return on your effort and investment.What 'enterprise agility' means for marketers, and how to thrive using lean and agile methods.What omni-channel marketing will mean in 2019.How AI platforms are going to disrupt marketing for the better.Panellists include:Jenny Williams, Chief Marketing Officer, Compare the MarketNigel Dalton, Chief Inventor, REA Group John Cosgrove, Partner - Salesforce Einstein, GrowthOps Panel Facilitator: James Gauci, Senior Digital ManagerPodcast Host and Event MC: Lisa Ma, Networx Brisbane & Iceberg EventsFurther resource links:Reload Media blog post: ‘Strategy and Innovation for 2019’ – Brisbane Networx November 2019Networx final top tips video: Strategy & Innovation for 2019+++This is a live recording at Loft West End on 27 November 2018 by Select Audio Visual.Networx Brisbane events are organised by conference and events company, Iceberg Events. These events are proudly supported by Reload Media, Vivo Group, Select Audio Visual, Vision6, Andzen and DPMA. Produced by Networx Brisbane, Australia. For upcoming live events, visit https://brisbane.networxevents.com.au/eventsFollow Networx Brisbane on Facebook, Instagram, LinkedIn and Twitter. Never miss an episode. Subscribe on Apple Podcasts, Spotify, Stitcher, Castbox or TuneIn to get new episodes as they become available.

Whether we're talking about customer service, marketing, or building developer teams, what we try to do on our AI in Industry podcast is bring to bear lessons that are transferable. There are few more transferrable ideas than what makes a company ready to adopt AI. When it comes to the willingness and the ability to integrate AI into a company strategy and to fruitfully adopt the technology to really see an ROI, what do the companies that do so successfully have in common? What do the companies that are not ready or too fearful to do it have in common? There are probably few companies in the AI vendor space that are aiming to sell AI more ardently into the enterprise than Salesforce, and there are few people that know more about how that process is going than Allison Witherspoon, Senior Director of Product Marketing for Salesforce Einstein, which is their artificial intelligence layer on top of the Salesforce product. We speak to Witherspoon about the telltale signs of a company that understands the use cases of AI in their industry and that have a good chance of driving value with AI. We also talk about the common qualities of companies that might not ready for I adoption. Read our full interview article on Sunday at Emerj.com

In business today, being data-driven can be a major factor in whether you and the company you work for succeed or fail. The wealth of information that’s now available is helping us make decisions big and small, strategic and tactical... but we didn’t have all of this data in the past and people were still making good decisions every day. Without a world full of data, people were just relying more on their gut, their instincts. Given this shift towards data and analytics in decision making, I wanted to understand – is one style of decision making now more effective than the other? To help me answer this question, I talked to a number of experts across different fields to get their take: Dr. Mary Lamia, a psychologist who has spent her career studying and encouraging emotional awareness. Dr. Lamia has joined us twice on the show before, back in episodes 9 and 12, to discuss emotions and motivational styles. Jen McDonald, the Executive Director of Client Engagement at global marketing agency VMLY&R. As a 20 year marketing veteran, she’s worked across a variety of industries and has been at the forefront of the digital and data revolution.   Kyle Loudermilk, the President and CEO of GSE Systems, which provides professional and technical engineering, staffing services, and simulation software to clients in the power and process industries. Steve Brown, a Director at Salesforce that’s inspiring growth of Salesforce Einstein by leading a team of talented Specialists committed to driving customer success. And Dana Cavalea, our guest in episode 24 and the former Director of Strength and Conditioning and Performance Enhancement with the New York Yankees Organization. Dana helped pioneer data-driven performance optimization in baseball, and now, Dana brings those same performance optimization techniques to business leaders, entrepreneurs, and pro athletes around the world. Learn more, and find the complete show notes, at flywheelassociates.com/podcast. Resources: Connect with Dana Cavalea: DanaCavalea.com | Twitter | Facebook | Instagram Connect with Steve Brown on LinkedIn Connect with Kyle Loudermilk on LinkedIn Connect with Jen McDonald: Twitter | LinkedIn Connect with Dr. Lamia at MaryLamia.com Subscribe to the Strategic Momentum podcast: On Apple Podcasts On the Google Podcasts On Stitcher Radio On Spotify Strategic Momentum is produced by Podcast Masters

Today we continue our TrainAI series with Sarah Aerni, Director of Data Science at Salesforce Einstein. Sarah and I sat down at the TrainAI conference to discuss her talk “Notes from the Field: The Platform, People, and Processes of Agile Data Science.” Sarah and I dig into the concept of agile data science, exploring what it means to her and how she’s seen it done at Salesforce and other places she’s worked. We also dig into the notion of machine learning platforms, which is also a keen area of interest for me. We discuss some of the common elements we’ve seen in ML platforms, and when it makes sense for an organization to start building one. The notes for this show can be found at twimlai.com/talk/143. For more details on the TrainAI series, visit twimlai.com/trainai2018

Shubha Nabar is a senior director of data science for Salesforce Einstein. Prior to working for Salesforce, she was a data scientist at LinkedIn and Microsoft. In the podcast she discusses Salesforce Einstein and the problem space that they are trying to solve, explores the differences between enterprise and consumer for machine learning, and then talks about the Optimus Prime Scala library that they use in Salesforce. Why listen to this podcast: * The volume of data, and hardware advances have made it possible to do machine learning to do them a lot faster. * AI is a science of building intelligent software, encompassing many aspects of intelligence that we tend to think of as human. * If you can’t measure something, you can’t fix it. * You have to think about what you can automate, rather than having a human to try and engineer out all those features. * Get feedback on design. Nora Jones, a senior software engineer on Netflix’ Chaos Team, talks with Wesley Reisz about what Chaos Engineering means today. She covers what it takes to build a practice, how to establish a strategy, defines cost of impact, and covers key technical considerations when leveraging chaos engineering. Why listen to this podcast: - Chaos engineering is a discipline where you formulate hypotheses, perform experiments, and evaluate the results afterwards. - Injecting a bit of failure over time is going to make your system more resilient in the end. - Start with Tier 2 or non-critical services first, and build up success stories to grow chaos further. - As systems become more and more distributed, there becomes a higher need for chaos engineering. - If you’re running your first experiment, get your service owners in a war room and get them to monitor the results of the test as it is running. More on this: Quick scan our curated show notes on InfoQ http://bit.ly/2vJoimw You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq Subscribe: www.youtube.com/infoq Like InfoQ on Facebook: bit.ly/2jmlyG8 Follow on Twitter: twitter.com/InfoQ Follow on LinkedIn: www.linkedin.com/company/infoq Want to see extended shownotes? Check the landing page on InfoQ: http://bit.ly/2xK7OxR

Nate Skinner, Vice President of Product Marketing at Salesforce, has been in B2B marketing for ten years with a focus on enterprise software, cloud, and mobile technology. Nate is responsible for B2B marketing for Salesforce, Pardot, and Einstein. Nate and I are diving into Salesforce Einstein Accounts Based Marketing (ABM). You’re going to learn what it is, how it’s used, and examples of Salesforce Einstein in action. If you’re a regular listener to this podcast, you’ve noticed that I’m paying quite a bit of attention to artificial intelligence (AI) and how it impacts marketing professionals and the sales process. I believe the lines are blurring between marketing and sales. My conversation with Nate provides more validation that we’re seeing the convergence of marketing and sales, and how AI and account-based marketing play a significant role in this convergence. View the show notes page: http://www.socialbusinessengine.com/podcasts/the-rise-of-account-based-marketing-through-ai

In this episode, we discuss developing lightning components with 3rd party frameworks, Salesforce Quick-Start implementations, the Salesforce FY18 Kickoff event, and IBM Watson and Salesforce Einstein partnership. LockerService and Lightning Container Component: Securely Using Third-Party Libraries in Lightning Components FY18 The Year Of Einstein IBM, Salesforce Strike Global Partnership on Cloud, AI IBM and Salesforce Announce Landmark Global Strategic Partnership Considerations for Setting Up Sales Cloud Einstein IBM Has Three Big Ways to Make Money Off Watson Computing

In this episode, we discuss fat-washing cocktails, FinancialForce's new CEO, Atlassian acquiring Trello, dueling with Salesforce support, and questions from the Good Day, Sir! Slack community. The Science of Fat-Washing Cocktails PDT’s Bacon-Infused Old Fashioned FinancialForce selects former Salesforce and Heroku exec to be new CEO Atlassian Acquires Popular Team Productivity App Trello For $425 Million Salesforce Einstein promises AI applications that 'just work'

Sam’s European river cruise & other adventures, Podcasteasy.com, Dreamforce ’16 report, Salesforce Einstein, MVPs, Twitter pass, DCLeaks and acquisition targets, government email security.