Third consecutive Best Buy-Side Programmatic Platform nomination follows Blockboard’s 2025 victory, while BlockVantage earns Best AI Tool recognition in its first year

NEW YORK, Sept. 16, 2026 /PRNewswire/ — Blockboard, the outcomes-driven advertising technology company built to bring greater trust, transparency and efficiency to digital media, today announced that it has been named a finalist in two categories at the 2026 Digiday Technology Awards:

Best Buy-Side Programmatic PlatformBest AI Tool – BlockVantage

The Best Buy-Side Programmatic Platform nomination marks the third consecutive year Blockboard has been recognized as a finalist in the category. It follows the company’s 2025 win, reinforcing Blockboard’s continued position among the industry’s leading programmatic platforms.

Blockboard’s growing trophy case also includes CEO and founder Matt Wasserlauf’s 2024 Digiday Technology Award for Founder of the Year. Together, these honors reflect multiple years of recognition for the company’s technology, leadership and commitment to addressing some of digital advertising’s most persistent challenges.

“To be recognized by Digiday for a third consecutive year, and in two categories, is an incredible honor for our entire team,” said Matt Wasserlauf, founder and CEO of Blockboard. “Winning Best Buy-Side Programmatic Platform last year validated our approach to building a more transparent and accountable advertising ecosystem. This year’s recognition of both Blockboard and our BlockVantage AI campaign tool shows that we are continuing to innovate while staying focused on what matters most: helping marketers eliminate waste, reach real audiences and generate stronger results.”

Blockboard was named a finalist for “Development of Verified AI Media,” recognizing its approach to combining artificial intelligence with trust-verified technology. The platform is designed to help advertisers plan, execute and measure campaigns across connected TV, online video, display, mobile and audio while providing greater clarity into how their media investments are being used.

Every impression purchased through Blockboard is pre-validated to help ensure that an actual person is behind the view. This approach allows marketers to essentially eliminate exposure to advertising fraud and wasted spending while directing more of their budgets toward real audiences and measurable outcomes.

The company’s second nomination recognizes the launch of BlockVantage, its AI-powered media-planning and campaign-activation tool. In its first year, BlockVantage was named a finalist for Best AI Tool, an early milestone for a platform created to simplify the traditionally complex process of launching digital and streaming television campaigns.

BlockVantage enables businesses to build media plans, identify target audiences, generate creative and launch campaigns through a streamlined experience. By making sophisticated advertising technology faster and easier to use, BlockVantage expands access to capabilities that have traditionally required significant time, expertise and resources.

The two nominations represent both sides of Blockboard’s mission: advancing enterprise-grade programmatic advertising while making powerful media technology more accessible to businesses of all sizes.

The Digiday Technology Awards recognize the companies and platforms driving innovation across advertising, media and commerce. Winners of the 2026 awards will be announced on September 22.

About Blockboard

Blockboard is a New York City-based advertising technology company helping brands and agencies plan, execute and measure digital media with greater trust, transparency and efficiency. Its platform combines artificial intelligence, advanced audience targeting and trust-verified blockchain technology to reduce advertising fraud and waste while helping marketers maximize the value of every media dollar. Blockboard supports campaigns across connected TV, online video, display, mobile and audio through managed-service and self-service solutions. For more information, visit www.myblockboard.com.

team@myblockboard.com

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SOURCE BLOCKBOARD

78% organizations prioritize restoring systems over maintaining business operationsOnly 22% have tested how critical operations would continue during recoveryJust 3% say current plans are equipped for frontier AI threats

SINGAPORE, Sept. 17, 2026  /PRNewswire/ — Cohesity, the leader in AI and data security, today released its fifth annual Cohesity Global Cyber Resilience Report, finding that 78% of organizations focus cyber recovery efforts on restoring systems rather than maintaining business operations. Restoring systems alone, however, does not guarantee a business can resume normal operations. Recovery depends on more, including whether restored environments can be verified as clean and safe, applications and dependencies are functioning properly, and employees have reliable access to systems and data.  

The independent study, conducted by Vanson Bourne, surveyed 3,200 IT and security decision-makers across 12 countries. The research examined where recovery plans fall short during actual attacks, how organizations define business continuity during recovery, and how well current plans account for AI systems and emerging frontier AI threats. The findings were announced at Cohesity Catalyst 2026.

“The research makes clear that many organizations still view recovery as a technology exercise when it is fundamentally a business imperative,” said Vasu Murthy, chief product officer, Cohesity. “True resilience is measured by an organization’s ability to continue operating, meet customer commitments, and recover quickly during a cyber crisis. AI makes the challenge more urgent by increasing the speed of attacks while adding new systems, data, and workflows. That same speed and scale is why AI also has to be part of the answer — strengthening how organizations detect, recover, and restore trust at machine speed.”

Restoring systems does not mean the business has recovered

The research found that organizations may struggle to resume normal operations even after systems are restored. Among those that experienced a material cyberattack in the past 12 months, 60% encountered moderate or significant delays because they lacked confidence that restored data and systems were clean and safe to use. Sixty percent also reported identity or access issues after systems were restored.

The scope of affected systems expanded beyond the initial assessment for 70% of those organizations. At the same time, an average of 61% identified moderate or significant gaps in how their plans accounted for cloud infrastructure, SaaS applications, identity services, security tooling, third-party integrations, and AI systems. For recovery teams, changes in scope or incomplete dependency information can affect what is restored, in what order, and what must be revisited as the response progresses.

These recovery complications are significant because most plans depend on conditions that may not hold during an actual attack. Across the full sample of surveyed organizations, 93% said their cyber response and recovery plans rely on all five assumptions examined in the research: containment, dependency visibility, recovery sequencing, decision-making clarity, and trusted restoration.

The business side of recovery is rarely formalized and tested

A Minimum Viable Company (MVC) helps organizations narrow the scope of recovery to minimize business disruption by defining what must be restored first. While 37% of research participants have formally documented an MVC, only 22% have both documented and tested it. Among that group, 64% said their MVC directly determined what was prioritized and restored first during a material cyberattack. The findings suggest that defining and testing an MVC can influence recovery priorities, but only if organizations operationalize it during an attack.

AI is becoming operational before it becomes recoverable

Recovery priorities must also account for the technologies the business increasingly depends on. The research found that although AI is widely used, it is not yet comprehensively addressed in most recovery plans. AI systems, applications, workflows, or machine learning models are now used by 99% of organizations, yet only 39% say their cyber response and recovery plans comprehensively account for attacks targeting them.

Organizations also reported readiness gaps when responding to AI-related incidents, with 56% saying they are not well prepared to detect, contain, and recover from unintended or incorrect actions taken by AI agents, copilots, or AI workflows. Similarly, confidence in verifying the integrity of AI models and related data following a cyberattack was low, with 58% reporting they were not very confident.

Frontier AI raises the stakes for recovery planning

Organizations expect frontier AI to place further pressure on existing recovery approaches. Eighty-three percent said their plans would require moderate or significant changes to address attacks involving capabilities such as vulnerability discovery, exploit development, and multi-step intrusions. Only 3% of respondents said their current recovery plans are equipped for those conditions.

Download the full Cohesity Global Cyber Resilience Report for deeper insights into cyber response and recovery, operational resilience, and AI readiness.

Methodology: Cohesity commissioned Vanson Bourne to survey 3,200 IT and security decision-makers at organizations with 1,000 or more employees across Australia, Brazil, France, Germany, India, Japan, Saudi Arabia, Singapore, South Korea, the United Arab Emirates, the United Kingdom, and the United States in July 2026. For the purposes of this research, a material cyberattack was defined as having a measurable financial, reputation, operational and/or customer churn impact on their organization.

About Cohesity

Cohesity protects, secures, and provides insights into the world’s data. As the leader in AI and data security, Cohesity helps organizations strengthen resilience, accelerate recovery, and reduce IT costs. With Zero Trust security and advanced AI/ML, Cohesity Data Cloud is trusted by customers in more than 140 countries, including two-thirds of the Global 500. Cohesity is also backed by industry leaders such as NVIDIA, Amazon, Google, IBM, Cisco, and HPE.  

Cohesity is certified as a Great Place to Work in multiple countries. Follow Cohesity on LinkedIn and visit www.cohesity.com to learn more.   

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SOURCE Cohesity

-A Chinese Startup Enters the Global RSI Race.

BEIJING, Sept. 16, 2026 /PRNewswire/ — Apex Intelligence has completed its angel and angel-plus funding rounds, raising nearly US$50 Million in total. The angel round was co-led by IDG Capital, LinkX Capital and XtalPi, with participation from Decent Capital, SEE Fund, Monad Ventures, and Winsoul Capital. The angel-plus round was co-led by Zhongguancun Science City Fund, SCGC, and Shanghai Engine Fund.

Founded in June 2026, Apex Intelligence is building the next generation of self-evolving foundation models. Self-evolution refers to Recursive Self-Improvement (RSI), or models improving themselves. With a focus on scientific research and discovery, the company aims to move AI from an assistive tool to a co-researcher, and from accelerating what is known to discovering what is unknown.

Apex Intelligence will also visit leading North American universities—including Harvard University, MIT, Yale University, and Boston University—from September 17 to September 23 to meet with students, researchers, and academic research groups for talent recruitment and research collaboration.

AI’s Next Frontier Is Research

Centuries of technological progress have unfolded through successive S-curves opened up by scientific breakthroughs. Each S-curve spans three stages: scientific breakthroughs, research discoveries, and engineering implementation. Most AI today remains focused on engineering and execution, while the scarce breakthroughs in science and research still depend heavily on humans.

Apex Intelligence believes the next technological revolution will center on AI becoming a co-researcher and a native research engine—one that goes beyond accelerating familiar work to actively discovering unexplored directions. Research is the core driving force behind RSI.

Building AI Researchers, Not Just AI Assistants

Apex Intelligence believes that advancing AI’s general intelligence in R&D requires model training. Specifically, through mid-training and post-training, the company guides models to generate creative ideas and autonomously carry out the entire cycle of self-improvement: hypothesis, experimentation, validation, and iteration.

Over the long term, Apex Intelligence aims to build self-evolving foundation models whose collective research capabilities match, and progressively surpass, those of 100,000 top-tier AI scientists spanning disciplines, forming a scalable network of AI researchers. This is a long-term vision and goal, and the company is working toward it step by step. It represents a fundamental shift in the R&D paradigm, rather than an incremental improvement in efficiency. Potential applications span any field where R&D workflows can be structured and outcomes measured, including chip design and simulation, molecular R&D, and quantitative strategy iteration. These fields share three characteristics: high value, intensive demands on human expertise, and costly trial and error.

Apex Intelligence’s Self-Evolving AI System Approaches Capabilities of Leading Human Researchers

Apex Intelligence’s self-evolving AI system has delivered encouraging results in both AI for AI and AI for Math.

AI for AI

The system has autonomously produced research of a standard suitable for acceptance at leading AI conferences, demonstrating capabilities comparable to those of an AI PhD student. It has also autonomously achieved more accurate decisions before training, better strategies during training, and optimizations to the underlying GPU kernels. Across SimpleTES, NanoChat Autoresearch, GPUMode TriMul, and MLS-Bench, it has set new records or approached the best publicly reported results, outperforming solutions developed by or with contributions from Recursive Superintelligence, Tencent Hunyuan, Stanford, NVIDIA, and other organizations.

AI for Math

The AI system has produced a complete proof of the majorization conjecture, which had remained open for more than three decades, and achieved multiple breakthroughs in optimization theory, geometric topology, and other areas.

Apex Intelligence was founded by Yongchao Chen, an assistant professor at Tsinghua University’s School of Artificial Intelligence. His undergraduate and graduate education spans the University of Science and Technology of China and a joint Harvard–MIT training program. He has conducted research at Google DeepMind, Microsoft, and the MIT–IBM Watson AI Lab. The core team comes from leading universities including Tsinghua, Peking University, Harvard, and MIT.

Looking ahead, Apex Intelligence will continue investing in foundation models and compute, advance the training and iteration of recursively self-improving foundation models, build a high-quality research trajectory data infrastructure, and attract top talent from around the world. Guided by its founding mission to “Unlock Undiscovered Discovery,” the company is working to move AI from reproducing existing knowledge to autonomous scientific discovery.

Founder Quotes

“I have always believed that models taught by humans are ultimately limited by humans themselves. When we align them to human preferences, we lock their intelligence ceiling at our own level. No matter how much compute and data we add, we are only making them better at retaining existing knowledge. The limits of true intelligence can only be defined by the objective world. The first generation of large models replaces white-collar workers; embodied AI replaces blue-collar workers; and ASI will replace humanity’s most accomplished scientists. That moment will come sooner or later. Our job is to bring it closer.”

— Yongchao Chen, Founder of Apex Intelligence

About Apex Intelligence

Founded in June 2026, Apex Intelligence is a Beijing, China-based self-evolving foundation model company focused on next-generation industrial intelligence through recursive self-improvement.

For more information, please visit: https://apexin.ai/

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SOURCE Apex Intelligence