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Hans India
6 hours ago
- Business
- Hans India
xAI's 'Project Skippy' Sparks Employee Concerns Over Facial Data Use for Grok AI Training
Elon Musk's AI startup, xAI, is facing growing scrutiny after a new report revealed that employees were asked to film their facial expressions and emotional reactions to help train its conversational AI, Grok. The internal initiative, dubbed 'Project Skippy,' began in April and aimed to improve Grok's ability to understand and interpret human emotions through visual cues. According to a Business Insider report based on internal documents and Slack communications, more than 200 employees, including AI tutors, were encouraged to participate. They were asked to engage in 15- to 30-minute video-recorded conversations, playing both the user and AI assistant roles. The intent was to teach Grok how to detect emotional subtleties in human expressions and body language. However, the project has sparked unease among several staff members. Many employees expressed discomfort over the potential misuse of their facial data and were particularly concerned about how their likeness could be utilized in the future. Some ultimately decided to opt out of the initiative. One employee recounted being told during a recorded meeting that the effort was meant to 'give Grok a face.' The project lead assured staff that the videos were strictly for internal use and that 'your face will not ever make it to production.' They emphasized that the goal was to help Grok learn what a face is and how it reacts emotionally. Despite these assurances, the consent form given to participants raised red flags. The form granted xAI 'perpetual' rights to use the participants' likeness—not just for training but also in potential commercial applications. While the document stated that a digital replica of the individual would not be created, this clause did little to ease privacy concerns. Adding to the tension were some of the conversation prompts provided to employees. The topics were designed to evoke emotional expression but were seen by some as overly personal or intrusive. Suggested questions included: 'How do you secretly manipulate people to get your way?' and 'Would you ever date someone with a kid or kids?' The controversy comes just weeks after xAI introduced two lifelike avatars, Ani and Rudi, which simulate facial gestures and lip movements during conversations. These avatars quickly attracted criticism online when users discovered that they could be provoked into inappropriate behavior—Ani reportedly engaged in sexually suggestive chats, while Rudi made violent threats, including about bombing banks. In a separate incident, Grok was also under fire for producing antisemitic and racist responses, further intensifying public concern about the model's reliability and ethical programming. Adding to the debate, xAI recently launched Baby Grok, a version of the chatbot intended for children, stirring further discussions around the use and safety of emotionally responsive AI technologies. As AI continues to advance into more human-like territory, Project Skippy serves as a stark reminder of the ethical and privacy complexities that come with blending human likeness and machine learning.
India Today
9 hours ago
- Business
- India Today
xAI Project Skippy asked workers to record their facial expressions to train Grok, report says
Elon Musk's artificial intelligence venture xAI asked its employees to record themselves expressing emotions and having conversations, as part of an internal project to help train its AI chatbot Grok, Business Insider has reported. The initiative, internally known as 'Project Skippy,' was launched in April and involved over 200 employees. The goal was to teach Grok how to recognise and analyse human facial expressions and emotional cues. Workers, particularly AI tutors, who help train the company's large language model, were asked to film themselves in 15- to 30-minute conversations with colleagues, playing both the role of user and AI to internal documents and Slack messages that were reviewed by Business Insider, several employees were uncomfortable. Apparently, many even raised questions about how their likeness might be used in the future, and some chose to opt out project lead reportedly told employees in a recorded meeting that Skippy would help 'give Grok a face,' and that the video data could be used to eventually develop avatars of people. However, the engineer reassured workers that the recordings were only for internal training and would not be made public. 'Your face will not ever make it to production,' they said. 'It's purely to teach Grok what a face is.' Still, workers had to sign a consent form that granted xAI 'perpetual' access to their likeness. This included not just training purposes but also use in commercial products and services. While the form stated that the data would not be used to create a digital copy of the worker, it wasn't enough to allay xAI staff were guided on how to have natural conversations during the recordings. They were asked to maintain eye contact, avoid one-word replies, and were even given suggested discussion topics, some of which were apparently surprisingly personal or provocative, such as 'How do you secretly manipulate people to get your way?' or 'Would you ever date someone with a kid or kids?'The project came just weeks before xAI launched lifelike avatars named Ani and Rudi, which move their lips and make realistic gestures. Users on social media were quick to show that the avatars could be prompted into disturbing behaviours. Ani engaged in sexually suggestive conversations, while Rudi made threats of violence, including bombing banks. xAI, last week, also launched a chatbot for children called Baby Grok was recently caught in another controversy for making antisemitic remarks, which followed another instance of Grok passing racist comments in replies to users on X.- EndsTune In
Business Upturn
11 hours ago
- Business
- Business Upturn
Navatar Unveils AI-Powered CRM That Meets Dealmakers Where They Work From Outlook to Slack to CRM: Private Equity's First Truly Embedded Intelligence Platform For Salesforce
By GlobeNewswire Published on July 23, 2025, 10:30 IST LONDON and NEW YORK, July 23, 2025 (GLOBE NEWSWIRE) — Navatar, the leading cloud platform for private equity and investment banking, today announced the launch of its next-generation, fully AI-powered CRM. Designed to meet the fast-evolving needs of private capital markets, the new Navatar platform combines intelligence, automation, and usability—solving one of the biggest challenges firms face when trying to put AI to work: data. In a recent Harvard Business Review article, 'How Private Equity Firms Are Creating Value with AI', highlighting the industry's rapid embrace of artificial intelligence – from identifying targets to improving portfolio performance – the authors note a common bottleneck: without structured, usable data, AI tools can't deliver their full potential. 'Everyone wants to use AI, but few have the data to make it work,' said Alok Misra, CEO of Navatar. 'That's because most CRMs are still clunky, inflexible systems that require painful manual data entry. We built the new Navatar platform to break that cycle.' A Media Snippet accompanying this announcement is available by clicking on this link. Navatar automatically captures relevant information from Outlook, LinkedIn, Slack, call notes, documents and third-party data—turning your team's daily activity into structured, usable intelligence for AI to operate on. No more chasing team members to update fields or fill out forms. While many firms invested in legacy, highly customized CRMs, they've found themselves stuck: the systems are slow to change, hard to use, and often ignored by the very people driving deals. Navatar flips that experience on its head—offering: Built-in automation to eliminate manual data entry Automated multi-tagging for people, companies, deals and more Embedded AI across sourcing, diligence, fundraising, and portfolio management Fast time-to-value without the need for costly customization A modern user experience that keeps deal teams coming back AI Where You Work: Inside Outlook, Navatar or Slack Navatar combines the best of Salesforce AI (Agentforce 3) and Microsoft Copilot so dealmakers no longer need to log into a CRM to get intelligence. Whether working inside Outlook, Navatar or Slack, users receive real-time insights, recommendations, and automation—all natively delivered in the tools they already use. Within Microsoft Outlook Smart Relationship Insights : Get a 360° view of any contact—who knows them internally, recent interactions, open deals, and more—directly inside your inbox. : Get a 360° view of any contact—who knows them internally, recent interactions, open deals, and more—directly inside your inbox. Email Summarization & Action Suggestions : AI summarizes long email threads and suggests follow-ups, tasks, and next steps. : AI summarizes long email threads and suggests follow-ups, tasks, and next steps. Deal Context at Your Fingertips : See associated deals, stages, and pipeline status without leaving Outlook. : See associated deals, stages, and pipeline status without leaving Outlook. Automated Meeting Prep : Copilot briefs you before a meeting by pulling intelligence from emails, calendar invites, past notes, and CRM activity. : Copilot briefs you before a meeting by pulling intelligence from emails, calendar invites, past notes, and CRM activity. Task & Data Capture: Turn meeting notes and emails into structured CRM entries automatically—no copy-pasting. Within Navatar Thematic Deal Sourcing : Surface emerging trends and high-fit targets based on proprietary and third-party data analysis. : Surface emerging trends and high-fit targets based on proprietary and third-party data analysis. Predictive Scoring : Rank inbound deals or prospects by likelihood to convert, based on past behavior and firm strategy. : Rank inbound deals or prospects by likelihood to convert, based on past behavior and firm strategy. Relationship Intelligence : Auto-map referral paths, warm intros, and deal team connectivity using AI across your team's network. : Auto-map referral paths, warm intros, and deal team connectivity using AI across your team's network. Document Intelligence : Use natural language processing to extract key terms, risks, and summaries from CIMs, pitch decks, and earnings calls. : Use natural language processing to extract key terms, risks, and summaries from CIMs, pitch decks, and earnings calls. Pipeline Management : AI generated deal summaries for easy pipeline reporting. : AI generated deal summaries for easy pipeline reporting. Automated Task Management : AI creates tasks, follow-ups based on triggers. : AI creates tasks, follow-ups based on triggers. Portfolio Alerts : Get AI-generated notifications on portfolio company performance shifts or risk flags. : Get AI-generated notifications on portfolio company performance shifts or risk flags. Fundraising & LP Intelligence: Personalize LP communications, score investor engagement, and automate routine updates. Within Slack CRM Alerts in Slack: Receive pipeline updates, LP activity alerts, and portfolio company notifications directly in relevant Slack channels. Receive pipeline updates, LP activity alerts, and portfolio company notifications directly in relevant Slack channels. Conversation-to-CRM Linkage: Slack messages can be tagged and associated with deals, contacts, or tasks inside Navatar, making it easy to capture institutional knowledge. Slack messages can be tagged and associated with deals, contacts, or tasks inside Navatar, making it easy to capture institutional knowledge. AI Summaries & Actions: AI monitors key deal-related channels and suggests follow-ups, summaries, or actions. AI monitors key deal-related channels and suggests follow-ups, summaries, or actions. Frictionless Collaboration: Deal teams can share notes, escalate issues, or push tasks to CRM—all from Slack. 'We're not just embedding AI into a CRM—we're embedding it into the workflow,' said Misra. 'Whether you're in Outlook, Slack, or Navatar itself, the intelligence meets you where you are.' For more information on Navatar for Private Equity, please visit: Private Equity CRM About Navatar Navatar (@navatargroup), the CRM platform for alternative assets and investment banking firms, is a low-touch, high-impact intelligence engine purpose-built for private markets. Now fully AI-powered, Navatar captures intelligence automatically and delivers insights directly into Outlook, Slack, and CRM—transforming routine activity into firmwide intelligence. Built on Salesforce and integrated with Microsoft Copilot, the platform eliminates manual data entry, unifies deal and relationship context, and orchestrates complex workflows without disrupting how investment professionals work. Backed by over two decades of CRM expertise, Navatar is used by hundreds of global firms to drive institutional knowledge, gain early access to opportunities, and execute smarter, faster. For more information, visit TeamNavatar [email protected] Disclaimer: The above press release comes to you under an arrangement with GlobeNewswire. Business Upturn takes no editorial responsibility for the same. Ahmedabad Plane Crash GlobeNewswire provides press release distribution services globally, with substantial operations in North America and Europe.
Forbes
21 hours ago
- Business
- Forbes
What Dropbox, Notion, And Slack Got Right About Their First Users
getty Most startups don't fail because of bad technology. They fail because they never find a group of people who care . First users are the proving ground for any product. They show you what matters, what doesn't, and what to fix next. The early strategies used by companies like Dropbox, Notion, and Slack show how much intentionality goes into building that first layer of usage and how different those approaches can be. This article breaks down what these companies got right and what other early-stage teams can take away when thinking about their own launch and user development. 1. Start Narrow, Not Loud When Dropbox launched, they didn't go broad. Their first wave of traction came from a short demo video posted to Hacker News and Digg. This wasn't accidental - it was targeted. They knew the first users needed to be tech-savvy, early adopters who would give feedback and test edge cases. That 3-minute video brought in 75,000 signups almost overnight. More importantly, it brought in the right kind of users. Too many startups treat launch like a megaphone moment. In reality, it's a filtering tool. Who shows up first tells you everything about who you're building for and whether your message is resonating. 2. Use Waitlists To Shape Demand Notion didn't rush into the public spotlight. In its earliest days, it operated almost like an invite-only tool. The product wasn't fully ready, and the team used this constraint to their advantage. By keeping access limited, they created a natural feedback loop: users who got in felt invested, and their feedback helped shape the product. More importantly, this approach helped Notion focus on the quality of usage, not just the quantity. The team knew they didn't need millions of users; they needed depth with a few hundred. That focus set the foundation for a highly active user base, which became a powerful growth engine later on. 3. Build In the Open (But Not for Everyone) Slack's public release was preceded by a long period of internal use. It started as a tool built for Stewart Butterfield's own company (Tiny Speck), and only became a standalone product after proving its value internally. Once they released it more broadly, they were still selective in how they scaled awareness. Slack worked hard to earn teams who would use it all day, every day, not casual signups. That focus on embedded usage led to organic growth: early users became evangelists within their own companies, helping Slack spread without big budgets. This highlights a core lesson: depth of engagement matters more than breadth in the early days. 4. Your First Users Are Not Just Customers, They Are Collaborators Each of these companies treated their early users like contributors, not just test subjects. Dropbox emailed users personally. Notion founders jumped into user forums. Slack had team members in every support thread. These companies weren't just watching metrics - they were listening to what their clients were saying. Early adopters are often the people who shape product language, feature sets, and priorities. In fact, many of the best-performing startups built marketing messages directly from early user conversations.. 5. Support Can Be A Growth Lever What many teams miss is that user support in the early days isn't just a cost - it's a growth function. Notion's founders handled support themselves in the early months. This gave them a front-row seat to problems and a direct line to users. More importantly, it made early users feel like insiders, not just customers. When teams use support to build relationships instead of deflecting issues, they create loyal users. These are the people who write your first reviews, refer friends, and justify your pricing. No ad campaign beats that kind of user-driven distribution. 6. Product-Led Doesn't Mean Passive Dropbox, Notion, and Slack are all considered 'product-led growth' companies. But that doesn't mean they relied on organic usage alone. They engineered user experiences that encouraged sharing, referrals, and internal virality. Dropbox famously rewarded users with more storage for inviting friends. Slack made it seamless to spin up a new team workspace. A common misconception is that good products just grow. In reality, growth is designed. These companies built feedback, sharing, and engagement into the product from the start. Early users didn't just use the product; they helped spread it. These strategies are explored in more detail in our startup marketing guide , which covers how to turn feedback loops into positioning 7. Ignore Vanity Metrics Early On Across all three companies, the focus was on usage quality, not on downloads, press, or social buzz. Dropbox tracked how often files were shared. Slack looked at messages per user. Notion paid attention to how many people built their second or third document. These metrics were tied to retention, not reach. If your first users aren't coming back, you don't have a product yet. That's why successful early-stage teams obsess over engagement signals, even if the numbers are small.
Hamilton Spectator
a day ago
- Business
- Hamilton Spectator
MX Welcomes Mark Nelson as New Chief Technology Officer to Accelerate Platform Innovation
LEHI, UTAH, July 22, 2025 (GLOBE NEWSWIRE) — MX Technologies, Inc., today announced an important change in technology leadership with the appointment of Mark Nelson as its new Chief Technology Officer. He brings more than 25 years of experience building and scaling engineering and product teams in high-growth environments. 'Mark Nelson is the perfect addition to our MX leadership team. He brings a rare combination of deep technical expertise and proven leadership at scale,' said Ryan Caldwell, Founder and Chief Executive Officer of MX. 'He has built and led some of the world's most demanding engineering organizations, and his passion for building product-minded teams with a strong bias for execution makes him the ideal leader for our next chapter. I'm confident Mark will continue to accelerate our platform innovation, strengthen our client partnerships, and help us deliver even greater value as we work to empower the world to be financially strong.' Previously, Mark was Senior Vice President of Technology at Marqeta, where he led card issuing and payment processing, banking, risk, and data teams. Before Marqeta, he led engineering efforts at Tableau (a Salesforce company), focusing on integrating Tableau's technologies into Salesforce and Slack, and building out its marketplace. He also helped scale Twilio's data and billing platforms, as well as spent 12 years at Salesforce building hyperscale data infrastructure and shaping the early Salesforce Platform and CRM products. 'MX is a company known for its mission, taking ownership, and caring deeply about serving its clients, partners, and the industry at large. I'm thrilled to join MX at such a pivotal time. I see tremendous potential to unlock new value for our clients through data-driven innovation, platform extensibility, and a relentless focus on execution,' said Mark Nelson. Mark succeeds Chief Product and Technology Officer Wes Hummel, who played a key role in continuing to elevate MX's engineering culture to new heights — building on a legacy as a place where top engineers choose to build leading technology in one of the most impactful industries at a company with a powerful mission. Wes will remain a close partner during this transition. About MX MX Technologies, Inc. enables financial providers and consumers to do more with financial data. MX provides end-to-end solutions for financial institutions and fintechs to connect to, understand, and act on customers' financial data. To learn more, follow us on X and LinkedIn @MX or visit .
