Today’s Top Data Stories

Anomalo Raises $33 Million in Series A

Anomalo, a company leveraging machine learning to help businesses solve the data viability issue automatically, has raised $33 million in its Series A funding. Norwest Venture Partners led the investment with partnering participation from Two Sigma Ventures, Foundation Capital, First Round Capital, and Village Global. Anomalo was founded by two ex-Instacart employees. Elliot Shmukler serves as the current co-founder and CEO. Anomalo aims to ensure that there is no issue with the data that its clients are using. It connects enterprise data warehouses like Snowflake and runs a machine learning model to see what is normal for a specific dataset and reports when it locates any issue. 

 

Machine Learning Experts to Work With the Rising Sun Pictures

Two post-doctoral researchers from the Australian Institute for Machine Learning (AIML), Dr. John Bastian and Dr. Ben Ward, will now lead a new initiative launched by the Rising Sun Pictures relating to the application of Artificial Intelligence and Machine Learning. The goal will be to develop pipeline tools to streamline visual effects (VFX) production and create more photo-realistic visuals. Rising Sun Pictures’ managing director Tony Clark believes that AI has great potential to accelerate labor-intensive tasks and augment human creativity when it comes to VFX applications. While collaborating with RSP on visual effects sequences for Marvel Studios’ current box office hit Shang-Chi & the Ten Rings, Bastian, and Ward found a novel technique for facial replacement, used in high-intensity martial arts combat sequences.

 

Pasqal is the developer of neutral atom-based quantum technology. It has presented its case through a paper titled “Quantum evolution kernel: Machine learning on graphs with programmable arrays of qubits.” The study published in the paper looks at how a Quantum Evolution Kernel (QEK) can work as a more versatile and scalable procedure to build graph kernels and analyze graph-structured data on quantum devices as compared to classical computers. Published in the peer-reviewed APS Physics journal Physical Review, the study infers that QEK is stable against detection error and on par with graph kernels in its accuracy.

 

Strobes Raises Undisclosed Amount of Growth Capital from SucSEED Indovation Fund

Strobes is a machine learning-based vulnerability management platform. It has raised an undisclosed amount of growth capital from the Hyderabad headquartered SucSEED Indovation Fund. While Strobes plans to use this fund to gain traction in the US market, its overall aim is to reduce cyber security risks through effective and efficient vulnerability management. To achieve its aim, Strobes first aggregates security risks from all sources, removes duplicates, and prioritizes vulnerabilities. Next, combining that intelligence with machine learning, Strobes offers best-in-class top-level management with quantified risk knowledge and cyber risk scores. 

 

86% Organizations Have Increased their AI/ML Budget from 2020 to 2021

DataRobot, a leading AI Cloud provider has released a survey-based research report on the state of AI and ML in enterprises. The survey has explored more than 400 organizations across industries. The survey shows that 86% of the respondents’ organizations have increased their yearly AI/ML budget from 2020 to 2021. The survey also locates a growing, diverse, and often disconnected combination of infrastructure, tooling, and specific use cases requirements driving their deployment of AI/ML solutions.