Blackbaud unveiled its AI-driven fundraising platform at bbcon 2026, introducing Lantern, a language model built specifically for fundraising. Developed in partnership with Databricks, Lantern draws on more than 40 years of fundraising data to deliver tailored intelligence directly within customers' workflows. CEO Mike Gianoni said the goal is to help organizations make smarter decisions and drive greater social impact. The company also expanded its Agents for Good lineup and recognized nonprofit leaders through its Changemaker Awards.
In the data center power space, Navitas Semiconductor and Microchip Technology jointly developed an 800V reference design aimed at next-generation AI data centers. The 20-kilowatt platform converts 800V DC straight to a 6V server rail in a single converter, targeting up to 96% peak efficiency at full load. The design meets Open Compute Project standards and combines Navitas' gallium nitride devices with Microchip's digital signal controllers. Both companies plan to showcase the solution at an OCP Event in San Jose this October.
Navitas also reported that its high-power revenue grew over 50% year over year, with AI infrastructure becoming an increasingly important segment. The company estimates the AI data center power market could reach $3.5 billion by 2030, reflecting the rapid buildout of AI facilities worldwide.
On the cybersecurity front, a new study found that using a small set of well-chosen metrics can dramatically improve attack detection. Researchers evaluated 21 Natural Visibility Graph metrics on the CICIDS2018 dataset and found that a Top3 configuration achieved 97.148% accuracy while cutting runtime by over 96% compared to using all metrics. Clustering coefficient measurements emerged as the most effective indicators.
Citi analyst Stuart Kaiser highlighted power generation as the toughest bottleneck for AI development, estimating roughly $1 trillion in AI-related capital spending next year and nearly $4 trillion by 2030. His comments came as the Federal Reserve faces pressure from the AI industry's continued expansion despite record-high borrowing costs. The AI buildout's scale now rivals government spending on defense and healthcare, complicating monetary policy efforts.
Yandex introduced Sona, a generative recommender model that replaces the entire recommendation cascade with a single system. A seven-day A/B test on Yandex smart speakers showed a 4.53% increase in active users and 6.30% more total listening time. Meanwhile, NetApp emphasized that cyber resilience now depends on governing how AI agents use data, noting that many risks stem from agents acting unexpectedly at machine speed rather than from malicious intent.
Key Takeaways
- Blackbaud launched Lantern, a fundraising-specific language model developed with Databricks, leveraging 40+ years of fundraising data
- CEO Mike Gianoni stated the goal is to help organizations make better decisions and drive greater impact
- Navitas and Microchip unveiled an 800V, 20kW AI data center power reference design targeting 96% peak efficiency
- Navitas estimates the AI data center market could reach $3.5 billion by 2030
- A study found that just 3 metrics can achieve 97.148% accuracy in cyber attack detection while reducing runtime by 96%
- Citi estimates $1 trillion in AI capital spending next year and $4 trillion by 2030, with power generation as the hardest bottleneck
- Yandex's Sona generative recommender model increased smart speaker active users by 4.53% and listening time by 6.30% in A/B testing
- NetApp warns that AI agents acting unexpectedly at machine speed pose significant cyber risks
- The Federal Reserve faces challenges controlling inflation as the AI buildout continues despite high interest rates
- Blackbaud celebrated nonprofit organizations at bbcon 2026 through its Changemaker Awards and Outstanding Leadership Award
Blackbaud launches AI fundraising model Lantern at bbcon 2026
Blackbaud introduced Platform for Good and Lantern, a fundraising-specific language model, at bbcon 2026. Lantern was developed with Databricks and draws on over 40 years of fundraising data. The model aims to deliver tailored intelligence within customers' existing workflows. CEO Mike Gianoni said the goal is to help organizations make better decisions and drive greater impact. The event also featured panel discussions on responsible AI adoption.
Blackbaud reveals AI innovations and Changemaker Award winners
Blackbaud showcased Platform for Good, Lantern, and an expanded Agents for Good lineup at bbcon 2026 in Columbus, Ohio. The company celebrated social impact organizations through its annual Changemaker Awards, honoring groups like Le Phare and Boston University. Michelle Edgerton of the YMCA of the North received the Outstanding Leadership Award. CEO Mike Gianoni emphasized connecting data and AI to help organizations unlock more capacity. The conference brought together thousands of nonprofit professionals and technology leaders.
Navitas and Microchip unveil 800V AI data center power design
Navitas Semiconductor and Microchip Technology collaborated on an 800V reference design for AI data center rack power. The design converts 800V DC to 6V DC and aligns with the Open Compute Project standard. It combines Navitas GaNFast gallium nitride devices with Microchip digital signal controllers. The platform targets up to 96% peak efficiency at full load with 2,100 W/in power density. The companies will showcase the solution at Microchip's OCP Event in San Jose in October 2026.
Navitas and Microchip reveal 20kW AI data center power platform
Navitas Semiconductor and Microchip Technology launched an 800-volt power reference design for next-generation AI data centers. The 20-kilowatt platform converts 800V DC directly to a 6V server rail in a single converter. It targets up to 96% peak efficiency at full load by combining two conversion stages. Navitas' high-power revenue grew over 50% year over year, with AI infrastructure becoming a larger business segment. Navitas estimates the AI data center market could reach $3.5 billion by 2030.
Study finds compact metrics boost cyber attack detection efficiency
A new study evaluated 21 Natural Visibility Graph metrics for detecting cyber attacks using the CICIDS2018 dataset. Four importance analysis methods were used to rank the metrics, with a Consensus Ranking strategy. The Top3 configuration achieved 97.148% accuracy and reduced runtime by 96.06% compared to using all 21 metrics. The top metrics involve clustering coefficient measurements. The findings show that fewer, well-chosen metrics can improve both performance and efficiency in cyber attack detection.
Guide to AI Insurance Coverage for Policyholders
Insurers are limiting AI-related coverage through exclusions and sublimits. Businesses should carefully review their policies and renewal applications. They need to document AI use accurately and consider specialized AI coverage.
Citi's Kaiser Says Power Generation Is AI's Hardest Bottleneck
Citi estimates about $1 trillion in AI-related capital spending next year and nearly $4 trillion by 2030. Stuart Kaiser said power generation is the hardest bottleneck to fix for AI development. He noted that AI-related spending is committed for the next 12 to 24 months. Kaiser also highlighted bullishness around healthcare and AI drug development.
T2 Unveils Product Suite for Marketing Sector
T2 has introduced a new product suite designed for the marketing sector. The launch aims to provide marketing professionals with updated tools and subscription options. Telecompaper reported on this development in the telecommunications industry.
Yandex Introduces Sona Generative Recommender Model
Yandex launched Sona, a single generative AI model that replaces the entire recommendation cascade. Sona combines candidate generation and ranking into one system. A seven-day A/B test on Yandex smart speakers showed a 4.53% increase in active users and 6.30% more total listening time. The model uses a semantic tokenizer, history compression encoder, and a decoder with beam search.
Cyber Resilience Now Depends on Governing AI Agent Data Use
NetApp says cyber resilience now requires governing how AI agents use data. Many risks come from agents doing unexpected things at machine speed rather than malicious intent. NetApp's behavior-based policy engine flags unusual data usage patterns. The company also offers an autonomous ransomware protection service that uses AI to detect attacks. AI Data Engine can be deployed on existing NetApp systems with a free six-month offer.
A.I. Boom Defies High Interest Rates, Complicating Fed Policy
The Federal Reserve struggles to control inflation as the A.I. industry grows despite record high borrowing costs. Companies expanding artificial intelligence capabilities remain undeterred by elevated interest rates. This forces the Fed to potentially tighten economic policy even more. The burden falls on rate-sensitive sectors like housing and automotive. The A.I. buildout is so large it rivals government spending on defense or health care.
Sources
- A new AI model draws on more than 40 years of fundraising expertise
- Blackbaud Expands AI Leadership with Platform for Good™ and Lantern™ at bbcon 2026
- AI data-center power design targets up to 96% peak efficiency at full load
- NVTS Stock In Spotlight Today Following Microchip Collaboration – Everything That Investors Need To Know
- A Multi Method Importance and Performance Efficiency Analysis of Topological Metrics for Natural Visibility Graph Based Cyber Attack Detection
- Keep Your AI On The Ball: A Policyholder’s Guide To Artificial Intelligence Insurance Coverage
- Citi’s Kaiser Says Power Generation Is AI’s ‘Hardest Bottleneck To Fix’
- T2 unveils product suite for marketing sector
- Yandex Introduces Sona: A Single Generative Recommender That Replaces Entire Recommendation Cascade
- Cyber resilience now depends on governing AI agent data use
- High Interest Rates Aren’t Slowing the A.I. Boom. That’s a Problem for the Fed.
Comments
Please log in to post a comment.