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The EU’s strategic rebalancing of research partnerships with China

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In 2026, one of Europe’s most ambitious scientific ventures, Horizon Europe, a seven-year, roughly €93 billion framework dedicated to research and innovation, underwent a quiet but significant transformation. 

What had once been an open invitation to researchers across the globe now carries a more guarded tenor. 

In critical areas such as artificial intelligence, semiconductors, quantum technologies, and biotechnology, organisations based in China are no longer automatically eligible to receive EU funding, a sharp deviation from earlier years when Chinese participation was possible, albeit under evolving conditions. 

This change is neither arbitrary nor purely technical. It reflects the culmination of years of negotiation and strategic signalling in Brussels. 

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According to the European Commission’s own international cooperation guidance, cooperation with third countries like China has always been conditional; Chinese researchers may contribute, but they are required to enter as Associated Partners and often must bring their own funding where EU funding does not automatically apply. 

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Yet the updated participation rules go further. 

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In late 2025, the Commission codified conditions that essentially block Chinese institutions from receiving core Horizon Europe grants in sensitive clusters of research and innovation. 

In policy terms, the threshold for inclusion has shifted: European partners must now demonstrate that their collaborators are not owned or controlled by Chinese entities, creating de facto barriers for significant portions of bilateral work in cutting-edge fields. 

While cooperation is not extinguished outright, joint work continues in areas like climate science and agriculture under bilateral road-map mechanisms; this recalibration is telling. 

It amounts to Europe drawing boundaries around where it will share its most prized scientific infrastructure and intellectual capital and where it will withhold it. 

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The official justifications, as framed by Commission texts, lean heavily on concerns about research security, intellectual property protection, and the perceived risk of unintended transfers of strategic technology where civil and military boundaries blur. 

Viewed in isolation, these adjustments might read as bureaucratic fine-tuning. But in the broader context of EU policy, which straddles an ambition for open scientific cooperation and an emergent emphasis on strategic autonomy, they underscore a fundamental tension. 

Europe still champions collaborative discovery across borders, yet it acknowledges nowadays research ecosystem is intertwined with global power dynamics in once unimaginable ways.

Beyond the sharp edges of eligibility rules lies a deeper question: why does this particular rebalancing matter in practice

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Over the past decade, China has become increasingly visible in global scientific networks. Its researchers regularly co-authored papers with European counterparts, and its rapidly expanding domestic science base, often supported through state mechanisms, moved from peripheral to central positions in disciplines ranging from materials science to computational biology. 

Yet in the architecture of Horizon Europe that emerges in 2026, participation is no longer synonymous with access to EU funds.

Chinese entities still can contribute to research proposals, but they do so as Associated Partners and typically must bring their own financing, a distinction that subtly but fundamentally changes the incentives and power dynamics of collaboration.

In practical terms, the new rules change how research consortia form and operate. European institutions seeking to work at the frontier of emerging technologies must now factor in eligibility constraints when structuring partnerships

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Where once multinational consortia could mix researchers from across continents with minimal procedural friction, they now must design collaborations that either exclude certain partners from funding streams or justify their presence through alternative mechanisms. 

This places a renewed premium on legal expertise, consortium management, and alignment with EU strategic priorities, an additional administrative layer that did not exist to the same degree in earlier cooperation frameworks. 

These restrictions could have unintended intellectual or scientific consequences. When large research systems are pushed to the margins, there is a risk that parallel ecosystems evolve, with reduced interoperability between them. In the long term, this could alter citation networks, collaborative norms, and research mobility patterns. 

It could also prompt other powerful actors to adopt similar measures, reshaping the landscape of global science into distinct blocs defined by policy fences rather than open inquiry.

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It’s important to emphasise that the EU has not abandoned bilateral scientific engagement outright.

Mechanisms outside Horizon Europe,  including mobility schemes and targeted co-funding instruments designed to support researcher exchanges, continue to exist, and cooperation on transnational challenges such as climate change and biodiversity remains active. 

What has changed is the weight of strategic calculation in decisions about where and how to invest EU funding. As a result, science policy in Europe now sits at the intersection of research excellence, economic sovereignty, and geopolitical strategy.

For Europe’s research community, this presents a complex set of questions. Does tighter control over strategic collaborations strengthen the European innovation base? Or does it risk isolating European science from talent and knowledge flows? 

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The answer is unlikely to be binary. 

What is clear, however, is that Horizon Europe,  once known chiefly as a vehicle for excellence and discovery, is now also a mirror of shifting geopolitical realities, showing how science policy has become part of broader efforts to navigate uncertainty in a multipolar world.

In the end, the EU’s decision to redraw the terms of research partnership with China feels less like a closing door and more like a recalibration of Europe’s compass. It acknowledges a world in which scientific discovery and geopolitical currents are no longer parallel tracks but deeply intertwined. 

The Horizon Europe programme, once the grand symbol of open scientific cooperation, now also stands as a marker of strategic foresight,  a space where Europe seeks to balance openness with caution, curiosity with control.

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This turning point doesn’t signal a retreat from global engagement. 

What it does reflect is a modern realpolitik of research: where funding decisions are informed not only by scientific merit but by questions of security, reciprocity, and long-term technological sovereignty. 

In a scenery defined by rising competition over frontier technologies, Europe is choosing to hedge its bets, opening some doors wider, while tightening others. The future of scientific collaboration may be neither total isolation nor full openness but a nuanced choreography between cooperation and strategic self-interest.

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How Teachers Make Classroom Technology Work for Them

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Walk into any school and you will find teachers using classroom technology in very different ways. One teacher builds interactive lessons with embedded videos and real-time polls. Down the hall, another uses technology more selectively, focusing on core features that support daily instruction. Both are effective educators. Both deserve classroom technology that works for them — and their students.

The challenge isn’t that teachers need to change how they work; it’s that most classroom technology is designed with only one pathway in mind. When tools offer multiple entry points instead, they can meet teachers where they are while supporting a wide range of student needs.

Recently, EdSurge spoke with three educators who use ViewSonic’s interactive display technology in distinctly different ways: Rebecca Ganger, technology coach and Chromebook coordinator, who also teaches high school students to repair devices and sponsors her district’s middle school Technology Club; Elena Clemente, technology trainer with 29 years of teaching experience in early elementary grades; and Brendan Powell, elementary STEM teacher. Their experiences illustrate what becomes possible when technology adapts to people rather than demanding that people adapt to it.

EdSurge: Why is it important that classroom technology offers multiple ways to engage?

Powell: Students need an engaging system to help them improve their understanding, and it makes learning more fun. Interactive technology helps a lot with coding, so my students can work through problems with me and are more engaged when they actually get to do the examples. Giving students choices helps them understand different concepts and piques their interest.

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Clemente: Students learn in different ways, and teachers bring different approaches to their classrooms. While some students may prefer the interactive tools already displayed, others might prefer to choose which tool to use to demonstrate how to solve a math problem. The same goes for teachers. Some may prefer to use ready-made slides, while others prefer to create on the canvas. By offering choices, we allow both students and teachers to use technology in ways that make learning engaging.


Image Credit: ViewSonic

What makes technology feel approachable rather than intimidating for teachers at different comfort levels?

Clemente: As I have led several professional development sessions for teachers, I know that some want only the basics, such as writing on the canvas or projecting slides. Others have created engaging lessons that bring learning to life. All teachers are able to learn more.

I have found that it is best to demonstrate how to use a tool on the interactive panel, have teachers practice and then discuss how they can use it in their lessons. When teachers take that learning back to their classrooms and apply it in a lesson, the tool feels more approachable.

Ganger: Often, new technology requires you to learn so many things just to be able to use the basics and get started. Being able to use parts of the software and then incorporate more as you become familiar and comfortable is a huge plus. You can start with just a little bit of instruction and then learn more to incorporate additional tools into your lessons as you’re ready. You can use it at your comfort level, and it is also very user-friendly for student participation at the board.

What changes occur when students interact directly with classroom displays?

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Powell: When students use the display in my classroom, they are more willing to talk to each other about the process and explain their ideas more clearly.

Ganger: They become more focused on the activity and are excited to participate. Students are so accustomed to auditory and visual sources being their primary ways of obtaining information. Having the opportunity to interact with technology fits into their natural way of learning.

Clemente: One of the big changes I have seen, or rather heard, is the amount of conversation that takes place. Students are able to express their thinking out loud while building speaking and listening skills. Students take pride in being able to share and navigate the interactive panel.

How do you keep students actively involved during interactive lessons?

Ganger: I personally enjoy adding a variety of interactive tools. I incorporate sounds, videos and links to other sites all within my presentation. I also enjoy using game boards with subject-specific questions as review activities. Varying the activities keeps things fresh and interesting for students.

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Clemente: One way I keep students actively involved is by having them use their [individual] whiteboards to participate while I am projecting. Students know that they are accountable and that I am looking to call on them to share good examples and demonstrate their learning. I also use partner talks so that students can share what they are learning and gain different perspectives. Students love being called up to engage with the interactive panel, so I call them up in groups. They line up and take turns, or sometimes they work as a team and collaboratively solve the problem.

When it works well, how does technology change your teaching?

Clemente: When technology works well, it makes my job as a classroom teacher easier. I am able to easily share material, provide visually appealing interactive slides and engage with my students using hands-on learning activities that build their technical skills. As a technology trainer, I use technology to demonstrate how teaching can come to life, creating engaging lessons that have a positive impact on student learning.

Ganger: It frees up time typically spent lecturing in front of the room, allowing more one-on-one interaction with students. It provides immediate feedback and allows for easy differentiation of material. Being able to reach all types of learning styles with interactive boards and software is a game-changer.

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Powell: The technology that works well in my room has changed how my students access information and made learning more flexible for all of them. One thing I like to say in my room is that technology can help us learn new skills and ways of thinking that will benefit us in the long run. Technology is always evolving, so it helps to have my students involved with me as I’m learning as well.

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OpenAI forms “Frontier Alliances” with top consultancies

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OpenAI is broadening how it helps large organizations put artificial intelligence into real use. The company announced a new initiative, Frontier Alliances, teaming up with four major consulting firms, Boston Consulting Group (BCG), McKinsey & Company, Accenture, and Capgemini, to help enterprises move beyond pilot AI projects and embed intelligent systems deeply into business workflows.

The announcement, published on OpenAI’s own website, lays out the reasoning behind the push: having powerful AI models isn’t the main bottleneck anymore.

Instead, companies need help designing the strategy, integrating the technology across systems and data, redesigning workflows, and managing organizational change so that AI can actually deliver value at scale.

Central to this effort is Frontier, OpenAI’s enterprise platform for building, deploying, and managing AI agents, systems that act like “AI coworkers,” performing tasks across software tools, extracting context from business data, and handling workflows end-to-end.

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These agents are meant to go beyond simple chat or isolated automation, helping with customer support, sales processes, software development tasks, and more.

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In its official press release, OpenAI described several key points about the Frontier Alliances:

  • The program pairs OpenAI’s Forward Deployed Engineering (FDE) teams with consultants from BCG, McKinsey, Accenture, and Capgemini to help enterprise customers adopt AI reliably and at scale.

  • Each consulting partner will build dedicated practice groups certified on OpenAI technology, combining technical expertise with deep industry and transformation experience.

  • The alliances cover both strategy and operational execution; from planning AI adoption to integrating Frontier with core systems and training internal teams.

Leaders from each consulting firm feature prominently in the announcement, stressing that teams need more than just tools, they need governance, change management, and end-to-end support to embed AI into daily operations.

This marks a clear strategic shift for OpenAI. Earlier this year, the company introduced Frontier as a platform designed to give AI agents shared context and capabilities that go beyond isolated demos or narrow use cases.

But real world deployments require more than technology alone. Large enterprises often struggle with data silos, outdated systems, and the internal alignment needed to scale new technology.

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The Frontier Alliances are meant to bridge that gap.

Reuters notes that this move brings OpenAI closer to traditional enterprise software players and differentiates its enterprise offering from simple model licensing by leaning into operational support and integration.

The consulting partners bring decades of experience in transformation and change management, helping customers make AI part of the everyday workflow rather than a one-off experiment.

OpenAI’s approach reflects broader industry trends. Enterprises have spent recent years experimenting with generative AI tools, but many have yet to turn early pilots into sustained production use.

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By combining Frontier’s agent platform with consultancy know-how, OpenAI hopes to accelerate adoption and deliver measurable business impact more quickly.

Competition in enterprise AI services remains intense.

Companies like Anthropic, Microsoft, and Google are also targeting corporate customers with their own AI platforms and partnerships.

For OpenAI, the Frontier Alliances are a way to leverage trusted business networks and implementation experience, giving its platform a stronger path into large-scale deployment.

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AI for Cybersecurity: Promise, Practice, and Pitfalls

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AI is revolutionizing the cybersecurity landscape. From accelerating threat detection to enabling real-time automated responses, artificial intelligence is reshaping how organizations defend against increasingly sophisticated attacks.But with these advancements come new and complex risks—AI systems themselves can be exploited, manipulated, or biased, creating fresh vulnerabilities.

In this session, we’ll explore how AI is being applied in real-world cybersecurity scenarios—from anomaly detection and behavioral analytics to predictive threat modeling. We’ll also confront the challenges that come with it, including adversarial AI, data bias, and the ethical dilemmas of autonomous decision-making.

Looking ahead, we’ll examine the future of intelligent cyber defense and what it takes to stay ahead of evolving threats. Join us to learn how to harness AI responsibly and effectively—balancing innovation with security, and automation with accountability.

Register now for this free webinar!

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Temporal CEO Samar Abbas on the ‘massive platform shift’ in AI fueling the startup’s $5B valuation

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Temporal co-founders Maxim Fateev, CTO (left), and Samar Abbas, CEO. (Temporal Photo)

Temporal co-founders Samar Abbas and Maxim Fateev have been tackling the same distributed systems problem since their days at Amazon, Microsoft, and Uber. But the AI boom has put the problem “on steroids” as agents move to production, according to Abbas — and investors have taken notice.

Temporal last week announced a $300 million Series D round led by Andreessen Horowitz, pushing its valuation to $5 billion — up from $2.5 billion in October.

Temporal’s revenue increased more than 380% year-over-year, reflecting demand for infrastructure services from companies using AI agents that are taking on more responsibilities.

“There is a massive platform shift happening,” Abbas told GeekWire. “And there is a whole layer of infrastructure being developed right now.”

Temporal’s pitch is something it calls “durable execution,” a new category Abbas says is about giving developers a simpler programming model for long-running, distributed workflows. Instead of wiring together queues, databases, retry mechanisms, and timers to handle failures, engineers write their logic as normal code and Temporal makes it durable behind the scenes.

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Abbas and Fateev launched Temporal in 2019, after they helped build an open-source orchestration engine called Cadence during their time at Uber. The tool was used by companies including HashiCorp, LinkedIn, Airbnb, Coinbase, and others.

“Both of us have been obsessed about this problem space,” Abbas said, describing Temporal as “literally the fourth or fifth time we are building a similar system.”

During the cloud era, Abbas said, Temporal became a “reliability backbone” for developers building mission-critical applications. Now, as AI models get smarter and agents hit production, the company is seeing huge scale.

“We are kind of becoming the core piece of infrastructure which is powering the AI agentic wave,” Abbas said.

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Temporal’s customer base ranges from OpenAI, which uses the platform for image generation, to Replit, which uses Temporal to orchestrate coding agents over extended sessions.

“As long-running agents become a primary driver of enterprise value, the execution layer beneath them becomes indispensable,” investors with Andreessen Horowitz wrote in a blog post. “Temporal wasn’t built in reaction to generative AI; it was built to make complex systems durable. But the agentic era has made that need undeniable.”

Asked about a potential AI bubble and broader hype, Abbas pointed to customers like Abridge in healthcare, where doctors can focus on patients instead of note-taking. He also noted transformation across legal workflows, coding agents, customer support, and research.

“There is real value being delivered to real users,” he said.

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He envisions a future where “every human on the planet can be called a software developer” and the cost of building software keeps falling, driving demand for a reliable execution backbone.

Temporal is built as a remote-first company, with around 375 employees and 62 of them in the Seattle area. Abbas and Fateev have been based in the region for decades, and many early employees are here as well.

Abbas, who was previously CTO (he swapped roles with Fateev in 2024) said the software infrastructure expertise in Seattle is a good match for trends that Temporal is riding. “Seattle has the right ingredients of talent,” he said. “We’ll be doubling down and growing in the Seattle area.”

As for advice to other founders riding the AI wave, Abbas said it’s about getting clarity on how you deliver value and avoiding all other distractions. “Just know who your users are — are they able to drive value from the product you are building?” He said Temporal is laser-focused on that strategy — and it seems to be working.

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Ring’s Super Bowl Ad Generates So Much Backlash It Has Ended Its Partnership With Flock Safety

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from the millions-well-spent dept

Eight million ways to die.

According to AdWeek, the price for a 30-second commercial during Super Bowl LX has soared to $8 million, after NBC opened in the summer by offering spots for $7 million. As AdWeek notes, “due to demand, the company has already reached its cap for the number of spots that were available for advertisers to buy during the upfront season.”

$8 million for 30 seconds sometimes means turning a niche product into a national phenomena. The 30 seconds purchased by Ring went the other way. If you want to see how $8 million can be used to promote mass surveillance enabled by consumer products, here you go:

Sure, it looks pretty innocuous. And what could be better than turning Ring and Flock Safety’s network of cameras into a digital proxy for posting “LOST DOG” signs all over the neighborhood? Well, as it turns out, pretty much everyone saw how problematic this offering was, especially considering what’s already known about Ring, Flock Safety, and both companies’ rather cavalier attitude towards privacy and other aspects of the Fourth Amendment.

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To begin with, the “Search Party” feature that allows people to access recordings and images captured by other people’s cameras is already on, which likely comes as a surprise to owners of these devices. Here’s what The Verge’s Jennifer Tuohy discovered last October, shortly after Ring announced its partnership with Flock Safety — a company best known for allowing cops to hunt down people seeking abortions and/or allowing federal officers to perform nationwide searches for whoever they might be looking for (which, of course, would be anyone looking kinda like an immigrant).

[I]t turns out that Search Party is enabled by default. In an email to customers this week, Siminoff wrote that the feature is rolling out to Ring outdoor cameras in November and noted, “You can always turn off Search Party.”

I checked my cameras this morning, and they were all automatically set to enable Search Party. And I’m not alone; Ring users on Reddit have also reported that their cameras have been enabled for Search Party

This under-reported “feature” was exposed by Ring’s Super Bowl ad, which resulted in enough backlash that Flock Safety no longer has a Ring to wear. Back to Jennifer Tuohy and The Verge:

In a statement published on Ring’s blog and provided to The Verge ahead of publication, the company said: “Following a comprehensive review, we determined the planned Flock Safety integration would require significantly more time and resources than anticipated. We therefore made the joint decision to cancel the integration and continue with our current partners … The integration never launched, so no Ring customer videos were ever sent to Flock Safety.”

While that last sentence may be true, it appears sharing was on by default when it came to Ring’s own cameras. That Flock Safety never got a chance to participate is good to know, but “Search Party” has apparently been active since its implementation last year, even if it was limited to Ring devices.

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And while Ring claims the Search Party feature can’t be used to search for “human biometrics,” that’s hardly comforting when it appears Ring definitely wants to add more of this kind of thing to its existing cameras.

On top of this, the company recently launched a new facial recognition feature, Familiar Faces. Combined with Search Party, the technological leap to using neighborhood cameras to search for people through a mass-surveillance network suddenly seems very small.

Ring insists this is not another mass surveillance tool, but rather something that attempts to recognize who’s at any user’s door when sending alerts, in order to differentiate friends and family members from strangers who might be within camera range. Again, there’s some utility to this offering, but the tech lends itself to surveillance abuses, especially when law enforcement may only be a subpoena away from accessing images and recordings captured by privately-owned devices.

Finally, the statement given by Ring only states that this won’t be happening right now, which is a wise choice considering its unpopularity at the moment. But that doesn’t mean Ring and Flock won’t seek to consummate this marriage of surveillance tech, albeit in a more private fashion that doesn’t involve alarming hundreds of millions of sports viewers simultaneously.

Filed Under: alpr, doorbell cameras, law enforcement, mass surveillance, surveillance abuse

Companies: flock safety, ring

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The Data Behind Social Proof: What Marketers Should Measure

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In today’s world, where more and more lives are online, social proof is very important. Things like likes, shares, reviews, and follower counts show what people think about something. These signs help people feel trust and want to join in. But, many do not read these numbers in the right way. Some feel short-term jumps matter most, but they miss seeing steady growth that can last. To get the best out of this, marketers need a clear plan for checking, giving credit, and trying out new ideas.

Social Proof Metrics

Social proof is not only about numbers that look good. It shows how people see your trust and fame. But the kind of feedback you get is not always the same. Likes and comments of how many followers you have have all given useful clues. Still, you have to look at the whole story to make the best choices.

  • Conversion rate: Tracks if social proof makes people do things we want, like signing up, downloading, or buying.
  • Retention metrics: Shows if the first interest turns into regular use or keeps people coming back over time.
  • Sentiment analysis: It looks as if the social proof shows good or bad feelings from people.

By looking at these numbers, marketers can see the difference between quick jumps in activity and real engagement. Stormlikes help them know what their audience truly cares about.

Attribution Challenges in Social Proof

One of the biggest challenges when using social proof is knowing where to give credit. Many campaigns can give a short burst of attention, but it’s very important to find out if these jumps in attention last over time. A lot of problems with tracking happen when people just look at simple numbers and do not link them to bigger business goals.

  • Last-click bias: Looking only at the last thing people do can make the effect of a social proof tactic appear bigger than it really is.
  • Channel overlap: Organic and paid campaigns often cross over, and this can make it hard to tell the effects apart.
  • Short-term spikes: A boost that happens for a short time, like from paid follower services or viral posts, may not show true growth in the long run.

Marketers need strong analytics systems to know which actions really help people buy and come back again, not just make the numbers look high.

Experimental Approaches to Measure Authentic Uplift

Testing is important when you want to see if your social proof ideas work. The only way to know the real effect of social proof on people is to do controlled experiments. This helps marketers find out what works and make choices using facts and data.

  • A/B testing: Compare content that has social proof and content that does not. This helps you see the differences in how people behave.
  • Time-based experiments: Add social proof slowly over time. Watch for short-term changes and also keep an eye on the bigger trends.
  • Geo or segment tests: Use social proof in certain groups or places. This lets you see the effect on people in one area or segment.

When you use these experiment ideas along with clear KPIs, you can tell the difference between short-term buzz and real growth.

KPIs to Track for True Social Proof

To make social proof work, marketers have to use both numbers and stories as key points. Do not look at just one simple sign, because that can give the wrong idea.

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  • Quality of engagement: Not every like means the same thing. Comments, shares, and mentions show more interest.
  • Follower growth rate: A steady increase in followers can say more than a quick jump.
  • Referral traffic: Shows if people come from social proof to take useful actions on your important pages.
  • Customer value over time (CLV): Links social proof campaigns to results that matter for your business in the long run.
  • Influencer amplification: Find out if popular supporters really help their followers trust the brand.
  • These numbers show how social proof works. Marketers can use this to make their campaigns better and get results that last.

Ethical Considerations for Practices

It is important to think about ethics when you try out ways to use social proof. If you use numbers that are not real, or if you show fake likes and shares, people will not trust your brand. Here are the best things you can do:

  • Transparency: Clearly tell people about any paid work or testing.
  • Gradual scaling: Try things out on a small scale to stop fake excitement.
  • Complementary strategy: Use social proof with top content and true messaging.

Ethical testing helps keep growth safe and steady. It makes sure your work fits with what people expect and trust.

Social proof can help your brand, but you cannot judge its effect just by looking at surface numbers. A platform like Stormlikes may help when you test things, but only if you use it in the right way and measure the results well. Knowing how the data behind social proof works helps marketers come up with plans that keep people engaged for a long time and make your brand look good. If you understand what driving action is, you will do better in the long run.

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There’s a sneaky way to watch Love Island All Stars final for free

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  • Stream Love Island All Stars finale free on ITVX
  • Watch ITVX when outside the UK with NordVPN (exclusive free gift)
  • Airs Monday, 23 February

The Love Island All Stars season 3 finale airs on Monday, 23rd February so expect more twists before we find out if frontrunners Sean Stone & Lucinda Strafford will be crowned champions. But did you know that some viewers can watch Love Island for free with this streaming hack…

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'How Many AIs Does It Take To Read a PDF?'

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Despite AI’s progress in building complex software, the ubiquitous PDF remains something of a grand challenge — a format Adobe developed in the early 1990s to preserve the precise visual appearance of documents. PDFs consist of character codes, coordinates, and rendering instructions rather than logically ordered text, and even state-of-the-art models asked to extract information from them will summarize instead, confuse footnotes with body text, or outright hallucinate contents, The Verge writes.

Companies like Reducto are now tackling the problem by segmenting pages into components — headers, tables, charts — before routing each to specialized parsing models, an approach borrowed from computer vision techniques used in self-driving vehicles. Researchers at Hugging Face recently found roughly 1.3 billion PDFs sitting in Common Crawl alone, and the Allen Institute for AI has noted that PDFs could provide trillions of novel, high-quality training tokens from government reports, textbooks, and academic papers — the kind of data AI developers are increasingly desperate for.

Read more of this story at Slashdot.

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Help us figure out macOS Tahoe 26.3 external drive mounting issues

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Some Mac users are discovering they can’t use their external drives with macOS Tahoe 26.3 and it seems Apple knows something’s wrong. Let us know what works for you, and what doesn’t.

An external drive connected to a Mac.
An external drive connected to a Mac.

Apple released the update to macOS Tahoe 26.3 on February 11, with the update adding more machine learning performance for M5 users as well as other smaller changes. It seems that one undocumented alteration may have caused problems for some users.
A number of users have taken to online support forums and social media to try and get help with an external drive issue in macOS Tahoe 26.3. Affected users are finding that external drives are not mounting properly, despite previously working fine.
Continue Reading on AppleInsider | Discuss on our Forums

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Nothing reveals the Phone 4a ahead of schedule

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Nothing has been slow-dripping news about the upcoming Phone 4a for a few days now, with a promise to reveal the handset on March 5. However, the company jumped the gun a bit and just posted an . It looks pretty nifty, even if we don’t have any real-deal specs just yet.

The image shows the handset from behind, displaying the company’s trademark transparent design. The picture also features the redesigned Glyph Bar, . This is a light-based notification system that features individually controlled mini-LEDs that light up in various ways to notify the user of missed calls and stuff like that. You can spot it next to the camera bump.

That’s about all we know right now, though there are plenty of industry rumors. It’s been reported that the Nothing Phone 4a will feature a and that the reveal will be accompanied by a Pro model with a more powerful camera. The Nothing Phone 3a was also launched alongside the 3a Pro.

We loved the 3a and 3a Pro, “an easy recommendation.” Let’s hope this carries through for the 4a. Also, you didn’t miss a release of the actual Nothing Phone 4. The company likes to release the a-series handsets . Past as prologue, we’ll likely see that one in early summer.

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