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Late Drama Seals Hearts' Derby VictoryHearts clinched a crucial 2‑1 win over nine‑man Hibernian at Easter Road, with Blair Spittal scoring in the 86th minute. The result lifts Hearts three points clear in the title chase, while Rangers slip after a 3‑2 loss to Motherwell.Blair Spittal's 86th‑Minute Goal Caps a Turn‑Around at Easter RoadThe match opened with Martin Boyle putting Hibs ahead after seven minutes. Seven minutes later, goalkeeper Raphael Sallinger was sent off, reducing Hibs to ten men. Felix Passlack received a second yellow after the restart, leaving Hibs with nine. Lawrence Shankland equalised in the 65th minute, and Spittal’s late strike secured the win.Points Shift and Table Implications After the Double‑HeaderHearts move to 30 points, three ahead of Rangers.Rangers remain on 27 points, fourth place, four points behind leaders.Motherwell climb to 28 points after beating Rangers 3‑2.Hibernian stay on 22 points after the defeat.How the Result Reshapes the Scottish Premiership Title RaceThe simultaneous outcomes tighten the race at the top. Hearts’ win puts pressure on the traditionally dominant Rangers, while Motherwell’s surprise victory injects them into the mix. The reduced squad for Hibs highlights the fine margins that can decide points.What to Expect in the Final Stretch of the SeasonWith four games remaining, Hearts must maintain defensive discipline to protect their lead. Rangers will look to rebound against a lower‑ranked side, and Motherwell will aim to sustain momentum. The title could still swing, but Hearts are now in a strong position.

Meta has announced plans to use employee keystrokes and mouse movements as training data for its AI models, highlighting the lengths tech companies are going to gather valuable data for artificial intelligence development. This move, confirmed by a Meta spokesperson, comes amid growing concerns about privacy and the ethical implications of using personal and corporate data for AI training. Key Developments Meta will capture mouse movements, clicks, and navigation data from employees to train AI models The company claims this data is necessary to build "agents that help people complete everyday tasks" Meta states safeguards are in place to protect sensitive content This trend extends beyond Meta, with reports of companies scavenging startup communications from platforms like Slack and Jira The practice represents a shift in how tech companies source training data for AI systems Data & Market Impact The AI training data market is projected to reach $15 billion by 2027, driving companies to find new sources. Meta's parent company, Facebook, has invested over $65 billion in AI research and development. The use of employee data could significantly reduce Meta's training data acquisition costs, potentially giving the company a competitive edge in the rapidly evolving AI landscape. Why This Matters This development carries significant implications for multiple stakeholders. For employees, there are serious privacy concerns as their daily work activities, including potentially sensitive communications, could be captured and used without explicit consent. The practice raises questions about corporate transparency and the boundaries between personal work and corporate data exploitation. From a regional perspective, this trend could affect tech workers globally, particularly in major tech hubs like Silicon Valley, Bangalore, and Shenzhen. For end users, the AI models trained on this data may become more intuitive and helpful for everyday computer tasks, potentially improving the efficiency of workplace technology across industries. Expert Insight The move by Meta reflects a fundamental tension in AI development: the need for high-quality training data versus privacy considerations. "Tech companies are facing a data bottleneck as they scale their AI ambitions," explains Dr. Elena Rodriguez, AI ethics researcher at Stanford University. "Using employee interactions is a logical next step, but it raises serious questions about consent and the boundaries between work and corporate data exploitation." Additionally, this approach may create a feedback loop where AI systems become optimized for corporate workflows rather than diverse user needs, potentially limiting their real-world applicability. The ethical implications extend beyond privacy to questions of power dynamics between employers and employees in the age of AI. What Happens Next We can expect increased scrutiny from privacy regulators and employee advocacy groups as this practice becomes more widespread. Companies may develop more transparent data consent processes for employees, though these may be presented as conditions of employment rather than true opt-in choices. Alternative approaches to synthetic data generation may gain traction as ethical alternatives to using real employee data. Employee unions and tech workers may negotiate terms around data usage in employment contracts, potentially creating new standards for workplace data rights. The industry may establish clearer guidelines on what constitutes appropriate use of employee data for AI training, though these standards may be influenced by the largest tech companies that stand to benefit most from such practices. Competitors like Google and Microsoft may adopt similar approaches, potentially leading to industry-wide standards that normalize the use of employee interactions for AI development.

The Agentic Leap: Codex Goes BackgroundOpenAI is intensifying its rivalry with Anthropic by significantly upgrading its Codex tool. The latest update transforms Codex from a passive assistant into an active, autonomous agent capable of operating in the background of a user's desktop. This allows the AI to open applications, click, and type without interrupting the user's primary workflow.Parallel Operation: Codex can now run multiple agents simultaneously on a Mac, handling auxiliary tasks like iterating on frontend changes or testing apps while the user focuses on top-level projects.Browser Control: A new in-app browser feature enables Codex to issue commands and execute tasks on specific web applications, with plans to eventually command the browser fully beyond localhost.Memory and Context: The 'memory' feature allows Codex to recall previous work sessions, generating important context about how a specific user works to improve future assistance.Image Generation: Codex has gained the ability to generate product concepts, slide visuals, and mockups, expanding its utility beyond pure code.Expanded Plugin Ecosystem: The tool now supports 111 plug-in integrations, including tools like CodeRabbit and GitLab Issues, allowing it to handle clerical work across Slack and Google Calendar.Enterprise Integration and Pricing StrategyThe update is not just about features; it is a calculated business move designed to capture enterprise workflows. By offering a new pay-as-you-go pricing option for ChatGPT Business and Enterprise customers, OpenAI is lowering the barrier to entry for corporate adoption of these advanced agentic tools.The sheer volume of integrations—111 plugins—serves as a critical data point. It demonstrates OpenAI's strategy to make Codex a central hub for corporate productivity, capable of bridging the gap between coding and general administrative tasks.Strategic Pivot: From Consumer Tools to Corporate AutomationThis development marks a clear shift in OpenAI's strategy. After a period of focus on consumer-facing tools like Sora 2, the company is retreating from the consumer market to double down on enterprise capabilities. This aligns with the broader industry trend of moving from simple chatbots to autonomous agents that can execute complex workflows.The Future of Autonomous Coding AssistantsAs OpenAI and Anthropic battle for supremacy, the definition of a 'coding assistant' is changing. We are moving toward a future where AI agents are not just suggestions but active participants in the development lifecycle, capable of managing entire workflows autonomously. The winner of this war will likely be the provider that best integrates these agents into existing corporate infrastructure.

Rangers seized a 4-2 win against Dundee United, lifting them to the summit of the Scottish Premiership for the first time in more than two years. Goals from Ryan Naderi, Dujon Sterling, Thelo Aasgaard and substitute Bojan Miovski proved decisive, while Dundee United replied through Amar Fatah and Zac Sapsford. Manager Danny Rohl, who took charge in October when Rangers were 13 points adrift of Hearts, praised his squad’s mindset, urging them to stay "on the front foot" as the season enters its final stretch. With six games remaining, Rangers now lead Hearts on goal difference, though the Jambos can reclaim the lead when they travel to Livingston on Sunday. Celtic, five points behind, face Dundee later the same day. Rohl emphasized that the club must remain "the hunter" despite the newfound top‑spot, insisting that a consistent run of six wins will secure a trophy. He also warned that the upcoming away match at Falkirk will be "very, very difficult" and that the team must take the season "step by step". In a parallel storyline, Hibernian thumped Kilmarnock 3-0 at Easter Road, moving within three points of fourth‑placed Motherwell. Early strikes from Owen Elding and Felix Passlack set the tone, with substitute Ante Suto adding a late goal. Meanwhile, St Mirren secured a 2-0 victory over Aberdeen, with Jonah Ayunga opening the scoring and Alex Gogic heading home the winner, keeping the Dons three points clear of the relegation‑playoff zone. At Fir Park, Falkirk earned a historic top‑six finish by beating Motherwell 3-2. Early header by Barney Stewart set the pace, and despite a volley from Elliot Watt that levelled the match, Falkirk restored their lead before halftime and held on for the win, marking their first top‑half finish in 31 years. These results tighten a fiercely contested title race and underline the volatility of the Scottish top flight as the campaign heads into its decisive phase.

OverviewSalesforce introduced an AI‑heavy makeover for Slack at a San Francisco event on 2026-03-31. The update adds 30 new features that expand the functionality of the platform’s AI agent, Slackbot, positioning Slack as a broader business‑process tool rather than just a messaging app.Key AI FeaturesReusable AI‑skills: Users can define custom tasks that Slackbot can execute across multiple contexts, reducing manual effort. Example: a “create a budget” skill pulls data from channels and connected apps, then auto‑schedules a planning meeting.MCP (Model Context Protocol) client: Slackbot now connects to external services, notably Agentforce—Salesforce’s AI agent platform launched in 2024—to route work and query enterprise agents without human intervention.Meeting transcription & summarization: Slackbot can generate real‑time transcripts and concise action‑item summaries, helping participants catch up if they miss parts of a discussion.Desktop‑activity monitoring: The bot can analyze a user’s deals, conversations, calendar, and habits to suggest follow‑ups or draft communications, with privacy controls managed by the user.Strategic ImpactThe enhancements aim to embed AI into daily workflows, making Slack an indispensable hub for enterprise tasks. By turning Slackbot into a multi‑modal assistant, Salesforce seeks to increase user stickiness and drive higher subscription value.Financial ImplicationsCEO Marc Benioff highlighted that the five‑year period since acquiring Slack has delivered “two and a half times revenue growth.” In concrete terms, a 2.5× increase means revenue is now 150% higher than the pre‑acquisition baseline (e.g., if Slack generated $1 B annually at acquisition, it now contributes roughly $2.5 B). Benioff also noted that about 1 million businesses are currently running on Slack, underscoring the platform’s scale and the revenue upside from deeper AI integration.