The AdCP workflow proposals launched with aplomb, but just what is the reality of where the market is at?

• Digiday
• 3 gün, 22 saat, 20 dakika

Over the last four months, Pacsun has developed tools and tweaked campaigns based on feedback from teenagers and twenty-somethings.

• Digiday
• 3 gün, 22 saat, 20 dakika

While a lot of the details seems familiar, it still doesn’t answer the inevitable unknowns.

• Digiday
• 3 gün, 22 saat, 20 dakika

The AdCP workflow proposals launched with aplomb, but just what is the reality of where the market is at?

• Digiday
• 3 gün, 22 saat, 20 dakika

TikTok news creators like Taylor Lorenz and Aaron Parnas on the platform's moderation and engagement woes, and how the new U.S. ownership could further affect that.

• Digiday
• 3 gün, 22 saat, 20 dakika

That shift is most visible in how the advertiser works with retailers, particularly British supermarket chain Tesco.

• Digiday
• 3 gün, 22 saat, 20 dakika

Robyn Freye was Stagwell’s chief growth officer who had a hand in winning clients such as Qualcomm and Expedia, and helped to build out Sports Beach.

• Digiday
• 3 gün, 22 saat, 20 dakika

Hints and answers to today's Hurdle all in one place.

• Mashable
• 3 gün, 22 saat, 21 dakika

Presented by Insight Enterprises Organizations today are trapped in proof-of-concept purgatory because yesterday’s models don’t work for today’s AI challenges. Everyone’s racing to prove what AI could do. But the real winners are those who have realized that AI deployment is not a technology project — it is a core operational capability. Success depends on execution, not just far-reaching visions of optimization. At Insight, we’ve seen this cycle before. For more than 35 years, from our roots as a Value-Added Reseller (VAR) to our evolution as the leading Solutions Integrator , we’ve helped clients cut through the hype and make emerging technology actually work. AI is following the same pattern. But this time, the stakes are higher, and the timelines are tighter. The organizations making real progress aren’t chasing pilots. They’re building the muscle to deploy, turning experiments and early momentum into measurable outcomes for the business. What every technology “era” has taught us about AI success MIT research estimates that 95% of enterprise AI initiatives fail to deliver measurable business value. This isn’t a failure of ambition. It’s a failure of deployment. Too often, leaders are stuck in the “what”, obsessing over which model to use or how fast they can automate a single task. They get locked into long, costly discovery phases with traditional consultants that are all about theory and very little action. We know this because we’ve lived it. When Insight first began experimenting with generative AI, our early pilots suffered from the same issues we see in the market: they looked great on slides but failed to scale. We also hit cultural resistance and skills gaps. To overcome this, we had to stop treating AI as a “tool” and start treating it as a “capability.” We started asking questions like, “ Where will AI truly change how our people work and how our business performs — and how do we get there now?” OR “Given the AI tech advances, what is the art of the possible? How can we re-imagine our business processes and the work our people do to drive 10x improvement? Now, 93% of our 14,000+ teammates are using generative AI tools in their daily work, saving more than 8,500 hours every week through automation and productivity gains. Building AI that actually delivers value If there’s one thing we’ve learned from decades of transformation, it’s that success isn’t born from strategy decks or proofs of concept. It’s earned in the details. As we brought together our AI experts from across our business, we saw that the most successful client engagements shared three common traits, but not the kind that fit neatly into a diagram. They’re about how work gets done: Fees tied to outcomes. The old model of billing for time and material is broken. Commercial models need to put skin in the game. We win when you see measurable business value, not when we complete project. Use tech to accelerate past theory. Instead of manual, multi-month discovery phases, look for partners who can accelerate your journey. We do this by providing our clients with an inventory of high-value use cases on day zero, so our consulting engagement starts with a roadmap to action, not just a listening tour. Look at internal transformation. You cannot successfully deploy for your customers what you haven't mastered internally. At Insight, we built our suite of AI offerings by first transforming our own business. Our internal story isn’t just a data point. It’s our proof of concept for cultural and operational change. It’s how we break the old perceptions and prove we understand the human side of deployment. In our 2024 survey of IT leaders , 44% identified skills gaps as a top barrier to transformation, and 74% said they have focused time and budget on building custom AI tools. Yet most still lack the deployment discipline to embed them. That’s the real craft of deployment. It’s not theory, and it’s not hype. It is execution at scale. And over the past few years, we’ve built on those lessons to give organizations a clear roadmap from ideation to ROI. Real success comes from connecting expertise, tools, and a robust delivery engine to get beyond vision and experimentation. The 70% that separates talk from transformation I love this concept from Boston Consulting Group (BCG) called the 10-20-70 rule. 10% of success comes from algorithms, 20% from data and technology, and 70% from people, process, and culture. Most companies invest nearly all their energy in the first 30%. But the real advantage (yes, the durable kind) lives in the 70%. That’s where execution happens. At Insight, we’ve built our entire business around that principle. From cloud to AI, our mission hasn’t changed. We turn technology into a capability that clients can scale and continuously improve. Turning AI potential into real-world results The “AI theory” era is ending. This next chapter belongs to the doers. To organizations ready to apply intelligence the same way they operationalized cloud or digital transformation. It requires a delicate balance of innovation and governance, and certainly bold ideas with disciplined execution. In fact, that philosophy is exactly what inspired Prism , our way of helping organizations bring clarity to complexity. Clients can get a full inventory of AI use cases for their entire business on day zero, skipping the months-long discovery phase of traditional consulting and prioritizing opportunities for immediate impact. We know that transformation doesn’t begin with algorithms. It begins with mastery, and it’s the kind we’ve earned through decades of deploying and scaling what’s next. How are you moving from hype to how? Joyce Mullen is President & CEO at Insight Enterprises. Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com .

• VentureBeat
• 3 gün, 22 saat, 21 dakika

Presented by Splunk Organizations across every industry are rushing to take advantage of agentic AI. The promise is compelling for digital resilience — the potential to move organizations from reactive to preemptive operations. But there is a fundamental flaw in how most organizations are approaching this transformation. We are building brains without senses Walk into any boardroom discussing AI strategy, and you will hear endless debates about LLMs, reasoning engines, and GPU clusters. The conversation is dominated by the "brain" (which models to use) and the "body" (what infrastructure to run them on). What is conspicuously absent? Any serious discussion about the senses — the operational data that AI agents need to perceive and navigate their environment. This is not a minor oversight. It is a category error that will determine which organizations successfully deploy agentic AI and which ones create expensive, dangerous chaos. Consider the self-driving car analogy. You could possess the world’s most sophisticated autonomous driving AI, but without LiDAR, cameras, radar, and real-time sensor feeds, that AI is worthless. Worse than worthless, it’s dangerous. The same principle applies to enterprise agentic AI. An AI agent tasked with security incident response, infrastructure optimization, or customer service orchestration needs continuous, contextual, high-quality machine data to function. Without it, you are asking agents to make critical decisions while essentially blindfolded. The three critical senses agents need For agentic AI to operate successfully in enterprise environments, it requires three fundamental sensory capabilities: 1. Real-time operational awareness : Agents need continuous streams of telemetry, logs, events, and metrics across the entire technology stack. This isn't batch processing; it is live data flowing from applications, infrastructure, security tools, and cloud platforms. When a security agent detects anomalous behavior, it needs to see what is happening right now , not what happened an hour ago 2. Contextual understanding: Raw data streams aren't enough. Agents need the ability to correlate information across domains instantly. A spike in failed login attempts means nothing in isolation. But correlate it with a recent infrastructure change and unusual network traffic, and suddenly you have a confirmed security incident. This context separates signal from noise. 3. Historical memory: Effective agents understand patterns, baselines, and anomalies over time. They need access to historical data that provides context: What does normal look like? Has this happened before? This memory enables agents to distinguish between routine fluctuations and genuine issues requiring intervention The hidden cost of data debt Here is where things get uncomfortable for most organizations: The data infrastructure required for successful agentic AI has been on the "we should do that someday" list for years. In traditional analytics, poor data quality results in slower insights. Frustrating, but not catastrophic. In agentic environments, however, these problems become immediately operational: Inconsistent decisions: Agents oscillate between doing nothing and triggering unnecessary failovers because fragmented data sources contradict each other. Stalled automation: Workflows break mid-stream because the agent lacks visibility into system dependencies or ownership. Manual recovery: When things go wrong, teams spend days reconstructing events because there is no clear data lineage to explain the agent’s actions. The velocity of agentic AI doesn't hide these data problems; it exposes and amplifies them at machine speed. What used to be a quarterly data hygiene initiative is now an existential operational risk. What winning organizations are building The organizations that will dominate in the agentic era aren't those deploying the most agents or using the fanciest models. They are the ones who recognized that agentic sensing infrastructure is the actual competitive differentiator. These winners are investing in four critical capabilities, all of which are central to the Cisco Data Fabric: 1. Unified data at infinite scale and finite cost: Transforming disconnected monitoring tools into a unified operational data platform is imperative. To support real-time autonomous operations, organizations need data infrastructures that can efficiently scale to handle petabyte-level datasets. Crucially, this must be done cost-effectively through strategies like tiering, federation, and AI automation. True autonomous operations are only possible when unified data platforms deliver both high performance and economic sustainability. 2. Built-in context and correlation: Sophisticated organizations are moving beyond raw data collection to delivering data that arrives enriched with context. Relationships between systems, dependencies across services, and the business impact of technical components must be embedded in the data workflow. This ensures agents spend less time discovering context and more time acting on it. 3. Traceable lineage and governance: In a world where AI agents make consequential decisions, the ability to answer "why did the agent do that?" is mandatory. Organizations need complete data lineage showing exactly what information informed each decision. This isn't just for debugging; it is essential for compliance, auditability, and building trust in autonomous systems. 4. Open, interoperable standards: Agents do not operate in single-vendor vacuums. They need to sense across platforms, cloud providers, and on-premises systems. This requires a commitment to open standards and API integrations. Organizations that lock themselves into proprietary data formats will find their agents operating with partial blindness. The real competitive question As we move deeper into 2026, the strategic question isn't "How many AI agents can we deploy?" It is: "Can our agents sense what is actually happening in our environment accurately, continuously, and with full context?" If the answer is no, get ready for agentic chaos. The good news is that this infrastructure isn't just valuable for AI agents. It enhances human operations, traditional automation, and business intelligence immediately. The organizations that treat operational data as critical infrastructure will find that their AI agents work better autonomously, reliably, and at scale. In 2026 and beyond, the competitive moat isn't the sophistication of your AI models — it's the operational data providing agents the insights to deliver the right outcome. Cisco Data Fabric, powered by Splunk Platform, provides a unified data fabric architecture for the agentic AI era. Learn more about Cisco Data Fabric . Mangesh Pimpalkhare is SVP and GM, Splunk Platform. Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com .

• VentureBeat
• 3 gün, 22 saat, 21 dakika

Yoolim Lee / Bloomberg : Sources: Samsung enters the final qualification phase to supply its HBM4 chips to Nvidia, and targets mass production in February; Samsung's shares jumped 3.2% —  Samsung Electronics Co. is getting close to securing certification from Nvidia Corp. for the latest version of its AI memory chip …

• Techmeme
• 3 gün, 22 saat, 30 dakika

The data shows Kubernetes consolidating its role in production, containers spreading across portfolios and GitOps moving from nice-to-have to maturity marker.

• Forbes Tech
• 3 gün, 23 saat, 26 dakika

Strava appears to be rolling out full route navigation and mapping to its watchOS app, bringing the long-awaited functionality to runners, hikers, and cyclists with Apple Watch for the first time. The feature, which remains in beta, allows users to select a pre-loaded route, view elevation details, and follow directions directly from their wrist without having to look at their iPhone. Strava users on Reddit noted the feature began appearing over the weekend . Since this time last year , Strava users have been able to share an Apple Fitness+ workout directly to the Strava app, but the ability to get turn-by-turn directions on an outdoor walk/run or bike ride feels like more of a game-changer for users of the fitness service. Both paying and non-paying Strava users currently seem to have access to the beta feature, but it's unclear whether it will be reserved for paying subscribers when finalized. Strava has yet to officially comment on the rollout. Tag: Strava This article, " Strava Apple Watch App Gains Route Navigation in Beta " first appeared on MacRumors.com Discuss this article in our forums

• MacRumors.com
• 3 gün, 23 saat, 31 dakika

"A Knight of the Seven Kingdoms" abandons an epic "Game of Thrones"-style title sequence, but there's a good reason.

• Mashable
• 3 gün, 23 saat, 46 dakika

"A Knight of the Seven Kingdoms" episode 2 has a hilarious exchange between Dunk and Egg that perfectly sums up their relationship.

• Mashable
• 3 gün, 23 saat, 46 dakika

The New England Patriots are headed to the 2026 Super Bowl. (Lauren Leigh Bacho via Getty Images) Lauren Leigh Bacho via Getty Images The New England Patriots and the Seattle Seahawks will face off in Super Bowl LX . For those of you who just can't with Roman numerals, that's Super Bowl 60, and it's taking place this year at Levi's Stadium in Santa Clara, CA, on February 8, starting at 6:30 p.m. ET. Like all other Sunday Night Football games this season, the championship game will be broadcast on Super Bowl Sunday on NBC, and will stream live on Peacock. And it's not just the game that we're excited for, either. This year's halftime performer is singer and rapper Bad Bunny, and there will be pre-game performances by Charlie Puth, Brandi Carlile, and Coco Jones. It's truly an incredible lineup of talent. Here's everything you need to know to tune in to Super Bowl LX when it airs on Feb. 8. How to watch Super Bowl LX Date: Sunday, Feb. 8, 2026 Time: 6:30 p.m. ET TV channel: NBC, Telemundo Streaming: Peacock, DirecTV, NFL+ and more 2026 Super Bowl game time The 2026 Super Bowl is set to begin at 6:30 p.m. ET/3:30 p.m. PT on Feb. 8, 2026. 2026 Super Bowl game channel The 2026 Super Bowl will air on NBC, with a Spanish-language broadcast available on Telemundo. 2026 Super Bowl teams: The New England Patriots and the Seattle Seahawks will play in the 2026 Super Bowl. Where is the 2026 Super Bowl being played? The 2026 Super Bowl will be held at Levi's Stadium in Santa Clara, CA, home of the San Francisco 49ers. What teams are playing in the 2026 Super Bowl? The teams for the 2026 Super Bowl will be determined after the AFC and NFC Championship games are played on Sunday, Jan. 25. You can keep tabs on the post-season playoff bracket here . How to watch the 2026 Super Bowl without cable You can stream NBC and Telemundo on platforms like DirecTV and Hulu + Live TV, both of which are among Engadget's choices for best streaming services for live TV . (Note that Fubo and NBC are currently in the midst of a contract dispute and NBC channels are not available on the platform.) The game will also be streaming on Peacock and on NFL+, though with an NFL+ subscription, you're limited to watching the game on mobile devices. Who is performing at the 2026 Super Bowl halftime show? Bad Bunny, who holds the title as the most-streamed artist in the world, will be headlining the 2026 Super Bowl halftime performance. You can expect that show to begin after the second quarter, likely between 8-8:30 p.m. ET. Singer Charlie Puth will also be at the game to perform the National Anthem, Brandi Carlile is scheduled to sing "America The Beautiful," and Coco Jones will perform "Lift Every Voice and Sing." Where to buy tickets to the 2026 Super Bowl: Tickets to the 2026 Super Bowl are available on third-party resale platforms like StubHub and Gametime. Find tickets on Stubhub Find tickets on Gametime More ways to watch Super Bowl LX This article originally appeared on Engadget at https://www.engadget.com/entertainment/streaming/how-to-watch-the-2026-super-bowl-patriots-vs-seahawks-channel-where-to-stream-and-more-173222330.html?src=rss

• Engadget
• 4 gün, 7 dakika