On Wednesday, the United Kingdom’s government announced a substantial investment of £225 million, equivalent to $273 million, in the development of an artificial intelligence supercomputer. This move underscores the nation’s commitment to establishing a leadership position in AI technology, as it endeavors to catch up with global leaders such as the United States and China.
The University of Bristol will be responsible for constructing this cutting-edge supercomputer, which is to be named Isambard-AI in honor of the renowned 19th-century British engineer Isambard Brunel. This announcement coincided with the commencement of the U.K.’s AI safety summit, hosted at Bletchley Park.
Isambard-AI, as indicated by the U.K. government, is poised to become the most advanced computer in the country. Once completed, it is anticipated to operate at a speed ten times greater than the current fastest computer in the U.K. The system will incorporate 5,448 GH200 Grace Hopper Superchips, potent AI chips developed by the leading U.S. semiconductor company Nvidia, known for its expertise in high-performance computing applications.
The construction of this supercomputer will be facilitated by Hewlett Packard Enterprise, a prominent American IT corporation, with the eventual aim of connecting it to the newly announced Cambridge supercomputer known as Dawn. The Dawn computer, engineered in collaboration between Dell and the U.K. company StackPC, will be powered by over 1,000 Intel chips utilizing water-cooling technology to enhance energy efficiency. It is expected to become operational within the next two months.
The U.K. government has high hopes that these combined supercomputers will play a pivotal role in advancing fusion energy research, improving healthcare capabilities, and enhancing climate modeling. These supercomputers are scheduled to be operational by the summer of 2024, according to the government, and will be instrumental in aiding researchers in the analysis of advanced AI models, conducting safety evaluations, and making significant strides in drug discovery and clean energy initiatives.
In a previous move, the government had allocated £1 billion to invest in the semiconductor industry, with the objective of securing the nation’s chip supply and diminishing its reliance on East Asia for critical microchips used in commercial applications.
In a landscape where conventional methods of outbound sales are losing momentum, Bluebirds, a startup founded by former LinkedIn leaders, is leading the charge by harnessing the power of AI. Today, the company proudly announces securing $5 million in seed funding from Lightspeed Venture Partners.
Established in 2022, Bluebirds distinguishes itself by employing AI to unearth distinct triggers that offer Go-to-Market (GTM) teams invaluable insights into the prospects they should target. This empowers them to engage the right individuals with the right message at the right time, all at an impressive scale.
The company has outlined its intention to utilize the funding to onboard skilled data and AI engineers, as well as introduce more triggers to its platform. This expansion aims to provide a comprehensive solution, assisting teams in building robust pipelines and expediting deal closures while reducing customer acquisition costs. The investment round also included the participation of Y Combinator, 1984 Ventures, SOMA Capital, and sales tech veterans Godard Abel and Dharmesh Shah.
A few years ago, sales representatives conducted widespread outreach by profiling potential customers and sending out cold emails and calls. While this approach proved effective, the current landscape presents challenges. Traditional outreach channels have become saturated due to increased competition, compounded by the integration of AI-driven spam filters.
During their tenure at LinkedIn, Kunal Punera and Rohan Punamia, the minds behind Bluebirds, engaged with numerous sales leaders and identified these shared obstacles. Subsequently, they launched Bluebirds to tackle these issues with AI-driven triggers, such as identifying past customers who trust the solution and recently switched jobs, compelling events extracted from SEC filings, and insights derived from job posting descriptions.
To generate these triggers, the company processes a vast amount of web data using a combination of Large Language Models (LLMs) and classical machine learning techniques. For example, the job change trigger offered currently necessitates users to upload a CSV file of their existing customers or connect their Salesforce instance. Once the contacts are integrated into the platform, Bluebirds’ proprietary algorithms pinpoint the most relevant options and match them with unique public profiles to identify job changes.
“If a job change is detected, another algorithm assesses whether it’s a legitimate one. Finally, the platform intelligently ranks the final leads based on an ideal customer profile score, created by analyzing past deals, enabling reps to focus on the most promising leads first,” Punamia explained to NextUnicorn.
Notably, Abel, the CEO of G2, employed the tool and identified 10,000 job change leads within 24 hours, ultimately generating $100,000 in pipeline revenue the following week. Presently, over 100 companies have embraced Bluebirds to attain similar benefits, including notable players like OneSignal, Front, Splash, and Simon Data, according to Punamia.
Interestingly, the AI tool’s basic offering is provided for free, allowing users to monitor an unlimited number of contacts for unlimited job change leads. However, to benefit from features like monthly updates of the job change list, human validation of leads, and Salesforce integration for distribution to GTM teams, customers will need to subscribe at a cost of $1,000 per month.
Bluebirds envisions continuing its innovative work by deploying the funding to expand its team with more data and AI experts and introduce new triggers for lead identification. Punamia expressed, “Intent extracted from job descriptions and compelling events from SEC filings are currently in beta testing, with several more triggers actively in development. Leveraging LLMs is a powerful technology, but using them effectively requires both art and science. We are rapidly pushing the boundaries of this technology to scale outbound efforts thoughtfully.”
While Bluebirds’ approach to outbound sales, centered on LLMs, is novel and distinct, it’s not the sole player dedicated to providing sales representatives with pertinent intelligence to enhance their ability to identify and close more deals. Other competitors in this space include ZoomInfo (which acquired Chorus for $575 million), Uplead, Outreach, and Apollo.io.
In the latest news, PortX, a fintech startup based in the Seattle area, has secured $16.5 million in fresh funding.
The investors leading this Series B funding round are Fuse, a venture capital firm based in Seattle that recently raised its own $250 million fund, and Curql, a collective of credit unions. Notably, BankTech Ventures, EJF Capital, and the Btech Consortium have also participated in this funding round.
PortX, under the leadership of CEO David Wexler, specializes in providing financial services infrastructure software to community banks, credit unions, and fintech companies. Their mission is to assist clients in implementing embedded banking-as-a-service solutions, reducing reliance on external vendors, and simplifying access to banking data. The new capital infusion will support various initiatives, including the enhancement of their AI offerings and data automation components.
In addition to this, with the support of Curql, PortX is establishing a Credit Union Service Organization (CUSO) aimed at better serving its credit union clientele. Curql manages a strategic investment fund that represents 68 credit unions and industry partners in the credit union sector.
PortX, headquartered in Mercer Island, Washington, was spun out of ModusBox the previous year. ModusBox, founded in 2013, initially focused on designing, developing, and supporting financially inclusive, national-level real-time payment networks.
Brendan Wales, a founding partner at Fuse, expressed his confidence in PortX, stating, “Their vision and technology align perfectly with the industry’s evolving needs.” He emphasized that this marks their second investment in PortX, highlighting their belief in the transformative potential of open banking in shaping the future of commerce and financial services.
As for the overall funding received by PortX, it now totals $26.5 million, including a previous $10 million from a Series A round conducted a year ago. Currently, the company employs a workforce of 78 individuals.
Secoda, a Toronto-based company specializing in AI-powered data search, cataloging, lineage, and documentation, has recently announced a successful Series A funding round, securing $14 million in investment. This capital infusion is earmarked for the advancement of its AI solutions, with the ultimate goal of enabling any enterprise user, regardless of their technical expertise, to seamlessly access, comprehend, and utilize company data. The user experience is designed to be as effortless as conducting a Google search.
This funding round brings Secoda’s total funding to $16 million and is spearheaded by its existing investor, Craft Ventures, with notable participation from Abstract Ventures, YCombinator, and Garage Capital. Distinguished figures from the data ecosystem, including Jordan Tigani (CEO of MotherDuck), Scott Breitenother (CEO of Brooklyn Data), and Tristan Handy (CEO of dbt), have also joined in this round.
Jeff Fluhr, co-founder and partner at Craft Ventures, emphasized the growing significance of data lineage understanding and data utilization for companies. He stated, “It has become increasingly important that companies not only have a full understanding of the lineage of their data from disparate sources but also harness their data to make more efficient and informed decisions. Secoda has built a powerful AI-powered data copilot for companies to do just that.”
In today’s enterprise IT landscape, numerous systems are designed for diverse functions, creating a complex web of technologies that are essential for organizational efficiency. However, this complexity often results in disconnected data sources, with applications failing to communicate effectively and data remaining isolated.
Consequently, employees face challenges when seeking answers related to data. They must navigate through convoluted applications or seek assistance from the data team, diverting attention from other tasks. Etai Mizrahi, who encountered similar issues while working at Acadium, described the frustration: “Questions that seem simple enough to answer end up feeling like a huge, frustrating game of broken telephone.”
Addressing the Knowledge Gap: To bridge this knowledge gap, Mizrahi collaborated with colleague Andrew McEwen to launch Secoda in 2021, offering an all-in-one platform for data management and search. Secoda seamlessly integrates with business intelligence and transformation tools, as well as data warehouses, effectively connecting all components of a team’s fragmented tech stack to establish a single source of truth for company data.
To simplify the process further, Secoda employs a ChatGPT-powered assistant, enabling users to create documentation that adds contextual information to metadata. Users can also search their company’s consolidated data catalog using natural language queries. Mizrahi highlighted the platform’s capabilities, stating, “Secoda does not simply give you information but gives you answers, much like Google… Our customers have been able to leverage the platform to reduce the volume of inbound data requests by over 40%, reduce onboarding times by 50%, and reduce time teams spend on documentation by 90% — huge time savings for data teams.”
With the recent funding injection, Secoda plans to bolster its engineering team and intensify research and development efforts, particularly in the area of AI enhancements. Additionally, the company intends to introduce “Secoda Monitoring” to assist data teams in ensuring the quality and accuracy of the data they use. This feature will provide insights into how changes affect assets and reduce data quality errors. Monitoring will also enable companies to track the operational efficiency of their data teams and identify potential cost savings.
Over the past year, Secoda has experienced substantial growth, expanding its customer base by a factor of five and managing over 100 million metadata resources, including tables, dashboards, columns, and queries. On the integration front, the data search tool currently supports 36 popular data warehouses, business intelligence tools, and productivity platforms, including Snowflake, dbt, and Looker. The company is committed to continually adding more connectors based on popularity and user demand.
HiddenLayer, a cybersecurity startup based in Austin, Texas, emerged in response to a cyberattack that exploited machine learning code at the founders’ previous company. Today, HiddenLayer has announced a successful $50 million Series A funding round aimed at bolstering the defenses of the ever-expanding array of AI models adopted by enterprises.
This funding round was spearheaded by M12, Microsoft’s Venture Fund, and Moore Strategic Ventures, with participation from Booz Allen Ventures, IBM Ventures, Capital One Ventures, and Ten Eleven Ventures.
HiddenLayer’s CEO and Co-Founder, Chris Sestito, expressed, “The rapid adoption of AI inspires us to accelerate our mission, ensuring that every security professional possesses the necessary tools and expertise to embrace AI securely.”
HiddenLayer already plays a crucial role in safeguarding AI/ML models for numerous Fortune 100 companies across various sectors, including finance, government, defense, and cybersecurity.
What HiddenLayer Offers:
Previously covered by VentureBeat, HiddenLayer has developed a suite of tools as part of its “MLSec” Platform, designed to safeguard enterprise machine learning (ML) and AI models. These tools do not directly access the models or compromise clients’ proprietary data and technology. Instead, they actively monitor the performance and operations of enterprise ML/AI models and associated applications in real-time. They scan for overarching vulnerabilities, provide recommendations for fortifying security, and detect the injection of malicious code/malware. Furthermore, they deploy defense mechanisms to thwart attackers and isolate intrusions.
HiddenLayer’s MLSec Platform includes an intuitive yet powerful dashboard, granting security managers immediate access to essential information about the security status of their enterprise ML/AI models. It automatically lists security issues and alerts in order of priority based on severity and stores data for compliance, auditing, and reporting purposes.
Additionally, HiddenLayer offers consulting services provided by their team of Adversarial Machine Learning (AML) experts, who remain up-to-date with the latest security trends and threats. These services encompass threat assessments, training for cybersecurity and DevOps personnel, and “red team” exercises to verify the effectiveness of clients’ defenses.
Earlier this year, HiddenLayer established a partnership with the prominent enterprise data lakehouse provider, Databricks. This collaboration enables Databricks enterprise customers to directly utilize HiddenLayer’s MLSec Platform for their models running on Databricks’ lakehouses. The integration is model-agnostic and covers model scanning, detection, and response. It empowers Data Scientists and ML Engineers to enhance their models’ security without altering their code or environment. As models are loaded, HiddenLayer’s model scanner ensures integrity and security. If an attack is detected, the integration responds automatically without human intervention.
Future Goals for Enterprise AI Security:
HiddenLayer’s inception traces back to an incident at its co-founders’ prior company, Cylance, where ML models fell victim to a cyberattack. Attackers exploited Cylance’s Windows executable ML model, revealing vulnerabilities and enabling the production of evasive binary files. While this event was concerning, it prompted the realization that attacks on ML/AI would escalate as more enterprises adopted generative AI to boost efficiency and performance.
Presently, HiddenLayer is experiencing rapid growth, having quadrupled its workforce in the past year. With the Series A funding secured, the company plans to hire an additional 40 personnel by year-end and continue expanding its client base.