At Google Cloud, we continue to invest in key technologies to progress towards our true north star on invisible security: making strong security pervasive and simple for everyone. Our investments are based on insights from our world-class threat intelligence teams and experience helping customers respond to the most sophisticated cyberattacks. Customers can tap into these capabilities to gain perspective and visibility on the most dangerous threat actors that no one else has. 

Recent advances in artificial intelligence (AI), particularly large language models (LLMs), accelerate our ability to help the people who are responsible for keeping their organizations safe. These new models not only give people a more natural and creative way to understand and manage security, they give people access to AI-powered expertise to go beyond what they could do alone. 

At the RSA Conference 2023, we are excited to announce Google Cloud Security AI Workbench, an industry-first extensible platform powered by a specialized, security LLM, Sec-PaLM. This new security model is fine-tuned for security use cases, incorporating our unsurpassed security intelligence such as Google’s visibility into the threat landscape and Mandiant’s frontline intelligence on vulnerabilities, malware, threat indicators, and behavioral threat actor profiles. 

Google Cloud Security AI Workbench powers new offerings that can now uniquely address three top security challenges: threat overload, toilsome tools, and the talent gap. It will also feature partner plug-in integrations to bring threat intelligence, workflow, and other critical security functionality to customers, with Accenture being the first partner to utilize Security AI Workbench. 

The platform will also let customers make their private data available to the platform at inference time; ensuring we honor all our data privacy commitments to customers. Because Security AI Workbench is built on Google Cloud’s Vertex AI infrastructure, customers control their data with enterprise-grade capabilities such as data isolation, data protection, sovereignty, and compliance support. 

Preventing threats from spreading beyond the first infection

We already provide best-in-class capabilities to help organizations immediately respond to threats. But what if we could not just identify and contain initial infections, but also help prevent them from happening anywhere else? With our AI advances, we can now combine world class threat intelligence with point-in-time incident analysis and novel AI-based detections and analytics to help prevent new infections. These advances are critical to help counter a potential surge in adversarial attacks that use machine learning and generative AI systems. That’s why we’re excited to introduce:  

• VirusTotal Code Insight uses Sec-PaLM to help analyze and explain the behavior of potentially malicious scripts, and will be able to better detect which scripts are actually threats. 
• Mandiant Breach Analytics for Chronicle leverages Google Cloud and Mandiant Threat Intelligence to automatically alert you to active breaches in your environment. It will use Sec-PaLM to help contextualize and respond instantly to these critical findings.

These new updates build on the existing AI in Google’s industry-leading solutions. For example, Chronicle Security Operations already uses frontline intelligence, integrated reasoning, and machine learning to identify initial infections, prioritize impact, and contain threats. Another example is reCAPTCHA Enterprise, which uses image noising capabilities to help protect your site from adversaries that leverage novel AI advances, greatly enhancing our defenses against bots. 

Adding intelligence to reduce toil

At Google Cloud, we help organizations modernize security wherever they are, in part by simplifying their security tools and controls whenever possible. Advances in generative AI can help reduce the number of tools organizations need to secure their vast attack surface areas and ultimately, empower systems to secure themselves. This will minimize the toil it takes to manage multiple environments, to generate security design and capabilities, and to generate security controls. Today, we’re announcing: 

• Assured OSS will use LLMs to help us add even more open-source software (OSS) packages to our OSS vulnerability management solution, which offers the same curated and vulnerability-tested packages that we use at Google.
• Mandiant Threat Intelligence AI, built on top of Mandiant’s massive threat graph, will leverage Sec-PaLM to quickly find, summarize, and act on threats relevant to your organization. 

These announcements build on existing capabilities that help customers centralize visibility and control, detect targets, and improve security across their platform. For example, Security Command Center (SCC) uses always-on machine learning to detect malicious scripts executing in the customer container environment and immediately alert the customer. In addition, Cloud Data Loss Prevention leverages machine learning to find and classify data, and with Confidential Computing you can collaborate on, train, and deploy sensitive and regulated AI models in the cloud, all while preserving confidentiality. 

Evolving how practitioners do security to close the talent gap 

At Google, we believe that to truly democratize security, we need to first acknowledge that AI will soon usher in a new era for security expertise that will profoundly impact how practitioners “do” security. Most people who are responsible for security — developers, system administrators, SRE, even junior analysts — are not security specialists by training. 

Imagine a world where novices and security experts are paired with AI expertise to free themselves from repetition and burnout, and accomplish tasks that seem impossible to us today. To help power this evolution, we’re embedding Sec-PaLM-based features that can make security more understandable while helping to improve effectiveness with exciting new capabilities in two of our solutions: 

• Chronicle AI: Chronicle customers will be able to search billions of security events and interact conversationally with the results, ask follow-up questions, and quickly generate detections, all without learning a new syntax or schema.
• Security Command Center AI: Security Command Center will translate complex attack graphs to human-readable explanations of attack exposure, including impacted assets and recommended mitigations. It will also provide AI-powered risk summaries for security, compliance, and privacy findings for Google Cloud.

These new releases bolster our existing efforts to tackle these issues through capabilities like IAM Recommender, which suggests permissions better suited to actual usage patterns. We will soon be augmenting this capability to cover organizational policies, further enabling the administrator to help improve the security posture of their organization. In addition, Mandiant Automated Defense applies machine learning to help reduce the repetitive Tier 1 alert triage problem and address alert fatigue. 

Offering availability 

VirusTotal Code Insight, available now in Preview, is our first example of putting Security AI Workbench to work for our customers. We will be rolling out other offerings to trusted testers in coming months, and they will be available in Preview more broadly this summer. Click here for the demo. 

Security AI Workbench, including Sec-PaLM and partner integrations, in addition to the product innovations described in our demo, are all building blocks for a larger effort to elevate security across the ecosystem. So far, that effort: 

• Provides assistive functions to rapidly develop IT generalist talent to Tier 1 security operator status in a way that wasn’t previously feasible. Security Command Center now can summarize threat intelligence insights and findings for Google Cloud, and Chronicle can quickly generate YARA-L rules or other detections. 
• Provides advanced functions such as iterative query and multivariate detection generation, conversational filtering and interaction with results, and smart case awareness to empower advanced Tier 2 and 3 security operators to focus on threat analysis instead of struggling with process and toil. Mandiant Threat Intelligence users now can elevate their core competencies to hunt, investigate, and remediate threats — using the same tools our own Mandiant experts use. 
• Fuses threat intelligence and AI-based analytic capabilities, which are unsurpassed in the market. VirusTotal Code Insight enables security teams to help gain insights and identify threats in suspicious code. This can significantly enhance their ability to detect and mitigate potential attacks.

However, this is just an initial step. We’ll continue to iterate and innovate, and we encourage customers and partners to leverage Security AI Workbench in new and exciting ways. Moving forward, we anticipate many new use cases to emerge over time. 

Building a safer future

While generative AI has recently captured the imagination, Sec-PaLM is based on years of foundational AI research by Google and DeepMind, and the deep expertise of our security teams. This work includes new efforts to expand our partner ecosystem to provide businesses with security capabilities at every layer of the cybersecurity stack. We have only just begun to realize the power of applying generative AI to security, and we look forward to continuing to leverage this expertise for our customers and drive advancements across the security community.

With more than 6 years of experience in building open source and Generative AI in education at scale, ibleducation.com continues to evolve its approach and services. More recently, the company became an education-focused Vertex AI integrator. They provide enterprises and academic institutions with a platform to build, train and securely customize large language models (LLMs) for interactive mentors using Google’s Vertex AI.

“The education industry only recently began understanding the value of Generative AI with open source and the opportunities it presents,” says Miguel Amigot II, Chief Technology Officer at ibleducation.com. “We’re providing the chance to build a new type of learning, mentoring, and analytics platform that gives organizations total control over their training methods, data, and more, without locking into one vendor.”

Organizations large and small, including Fortune 500 companies and leading universities institutions, use ibleducation.com to support their learners, allow educators to develop coursework, and provide engineers with a solid platform to build on.rely on it to power their learning strategies.

Recently, ibleducation.com chose to partner with Google Cloud to improve its platform and scale beyond its base of millions of users.

Harnessing the power of GenAI in education and training

ibleducation.com initially began working with Google Cloud to unify its education data strategy to drive real-time and predictive analytics. 

“Google Cloud outperforms others when it comes to maintaining control over algorithms and general data governance,” says Amigot.  “We’re fortunate to be able to maintain ownership of our models while maintaining a pay-per-use pricing model. This is critical for our business. It allows our clients to avoid lower-value maintenance tasks, focus on innovation and user experience, and not worry about excessive costs.”

In the past, because of the high costs and need for AI and engineering talent to produce large language models, schools have been unable to take full advantage of open-source education technologies. Together, ibleducation.com and Google Cloud democratize access to AI-enabled tools for educators worldwide.

With a strong analytics and AI foundation, ibleducation.com has been able to personalize, translate, and create education content faster than before. This has been especially effective in improving accessibility, as automated translation and repurposing ensures those with visual and hearing impairments can interact with the content. 

“Google Cloud enables us to reduce the total cost of building, running, and maintaining large language models by more than 70%,” says Amigot. “We’ve seen language model hosting costs decrease before, but nothing like this.”

Bringing AI-powered content creation to educators

Vertex AI has been especially useful in creating content, helping ibleducation.com to dramatically scale out its learning materials. Usage-based pricing mixed with an open-source model gives ibleducation.com the resources to support its users in developing evolving, valuable learning experiences to serve people worldwide.

Additionally, Google Cloud powers ibleducation.com’s Generative AI-based mentors, which provides a one-to-one learning experience to students and professionals looking for tailored skills development.

“The mission is to provide educators with a centralized system wherein they can manage everything from indexing data about customer courses to designing and facilitating UI/UX for users’ digital mentors,” says Amigot. “Google Cloud has helped us cover all of these bases.”

ibleducation.com allows users to create virtual mentors that provide personalized teaching, assess student knowledge, guide students through skills and learning paths, and offer robust learning analytics. Text-to-text and speech-to-speech interfaces can be offered over Slack, Discord, text message-based bots, web scripts, and LTI integrations. 

“AI Mentor has been a very effective tool for our users because it adapts to the needs of educators and organizations very quickly,” says Amigot. “We’re seeing people use it for teaching assistance, marketing and administration, and a lot more. Vertex AI allows us to have many models for any variety of purposes.”

Looking forward, ibleducation.com is looking to continue taking personalized learning to new heights.

“From a mission standpoint, we want to expand to reach all the organizations not currently served by online education through our platform, analytics, and other AI-powered services,” says Amigot. “Our relationship with Google Cloud is instrumental in achieving our goal to democratize access to next-generation educational capabilities to more communities and organizations around the globe.”

Ready to take the next step? Join our upcoming GenAI workshop for higher education to learn how Google’s AI tools can help education institutions or explore our EdTech solutions to see how you can make education more personal, safe, and accessible with 100+ cutting-edge products.

If you’ve ever used only your voice to authenticate a payment, place an order, or check an account over the phone, there is a good chance that Pindrop’s technology made it possible.

Founded in Atlanta in 2011, Pindrop provides software and technology that uses machine learning, voice recognition, and behavioral analytics to help detect and prevent fraud in voice channels like AI-powered call centers and solve the long standing identity problem commonly encountered in customer care and contact center experiences. Demand for Pindrop’s technology has grown considerably over the past decade, as more organizations and people adopt voice as an interface for customer service, transactions, entertainment and more. As that demand has grown, safeguarding these voice interactions from fraud or authentication loops continues to be a unique challenge.

Now, with frictionless voice-driven customer experiences at an all-time high, cybersecurity is more critical than ever. In fact, research shows that fraudsters are able to accurately answer knowledge-based authentication questions 92% of the time, as opposed to only 46% for actual customers. To address this, Pindrop is bringing its products and technology to Google Cloud in order to scale and develop new capabilities that will help enable the next wave of voice-first interfaces and call centers.

The new partnership will enable Pindrop’s teams to accelerate their development of new capabilities to address an ever-shifting landscape – like detecting deep fakes and robocalls, helping banks authenticate transactions, providing retailers with AI-powered call center support, and helping IoT makers optimize for security, speed and simplicity.

More specifically, the partnership will help Pindrop scale its own businesses, and meet ever-growing customer needs in several ways.

First, Pindrop is bringing its SaaS platform to Google Cloud, enabling customers to deploy it at global scale, on secure, sustainable, and highly performant cloud infrastructure. Not only does this give Pindrop the ability to deliver secure voice interactions with low-latency, it also aligns with its mission to enable customer choice when selecting and implementing security technology. And for customers already operating on Google Cloud, getting started with Pindrop can be done directly within their cloud environment, now that the company is making its solutions available on Google Cloud Marketplace.

Second, Pindrop plans to offer its voice secure technology with Google Cloud’s Contact Center AI (CCAI) capabilities to develop new solutions that will enhance call center experiences. CCAI capabilities in understanding, augmenting, and ML-processing conversations allows companies to deliver interactions that are helpful and keep costs low. These capabilities alongside Pindrop’s authentication and anti-fraud solutions will enable the company with the tools and technologies needed to create the next evolution of frictionless experiences in a secure way.

Finally, building on top of Google Cloud will equip Pindrop with multicloud capabilities that will offer new channels to increase revenues through. Using technologies like Google Kubernetes Engine, frequently chosen by startups and tech companies, to quickly launch and scale new ML applications up or down will also support Pindrop’s growth as it adds to its suite of technologies.

Supporting innovative startups and digital native businesses like Pindrop is in Google’s DNA, and we’re delighted to support Pindrops’ growth, and the success of their customers, with Google Cloud infrastructure, Contact Center AI, and go to market expertise.

You can learn more about Pindrop on Google Cloud here, and Google Cloud’s Contact Center AI solution here.

Data science can be applied to business problems to improve practices and help to strengthen customer satisfaction. In this blog, we address how the addition of Looker extends the value of your Google Cloud investments to help you understand your customer journey, unlock value from first-party data, and optimize existing cloud infrastructure.    

Data is a powerful tool 

While everyone doesn’t need to understand the nuts and bolts of data technologies, most people do care about the value data can create for them — how it can help them do their jobs better. Within the data space, we are seeing a trend of ongoing failure to make data accessible to “humans” –   the industry still hasn’t figured out how to put data into the hands of people when and where they need it, how they need it. 

What if everyone in your organization could analyze data at scale, and make more-informed, fact-based decisions?   Data and insights derived from data are valuable but only if your users see it.  We think Looker helps solve that. 

Solutions tell a larger story of how it all fits together 

Across all verticals and industries,  businesses benefit from knowing and understanding their customers better. Many business goals are to increase revenue by improving product recommendations and pricing optimization, improving the user experience through targeted marketing and personalization, and reducing churn while improving retention rates.  To help reach  these goals, key strategies should focus on understanding customer needs, their motivations, likes and dislikes, and using all available data – in other words, put yourself in the shoes of your customer.    

Our goal with Looker solutions is to offer the right level of out-of-box support that allows customers to get to value quickly, while maintaining the necessary flexibility. We aim to offer a library of data-driven solutions that accelerate data projects. Many solutions include Looker Blocks (pre-built pieces of code that accelerate data exploration environments) and Actions (custom integrations) that get customers up and running quickly and lets you build business-friendly access points for Google Cloud functionality like BQML, App Engine and Cloud Functions.  

Below, you’ll find a sampling of the newest Looker solutions. 

Listening to customers by looking at the data

Looker’s solution for Contact Center AI (CCAI), helps businesses gain a deeper understanding and appreciation of their customers’ full journey by unlocking insights from all their company’s first-party data. Call centers can converse naturally with customers and deliver outstanding experiences by leveraging artificial intelligence. CCAI‘s newest product —CCAI Insights — reviews conversations support agents are having, finding and annotating the data with the important information, and identifying the calls that need review. We’ve partnered with the product teams at CCAI to build Looker’s Block for CCAI Insights, which sets you on the path to integrating the advanced insights into your first-party data in Looker, overlaying business data with the customer experience.

Businesses can better understand contact center experiences and take immediate action when necessary to make sure the most valuable customers receive the best service. 

Realizing full business value of First-Party data

Looker for Google Marketing Platform (GMP) provides marketers the power to unlock the value of their company’s first-party data to more effectively target audiences.  The Looker Blocks and Actions for GMP offer interactive data exploration, slices of data with built-in ML predictions and activation paths back to the GMP.  This strategic solution continues to evolve with the Looker Action for Google Ads (Customer Match), the Looker Action for Google Analytics (Data Import) and the Looker Block for Google Analytics 4 (GA4).

• The Looker Action for Customer Match allows marketers to send segments and audiences based on first-party data directly into Google Ads. Reach users cross-device and across the web’s most powerful channels such as Display, Video, YouTube, and Gmail.  The entire process is performed within a single screen in Looker, and is able to be completed in a few minutes by a non-technical user. 
• The Looker Action for Data Import can be used to enhance user segmentation and remarketing audiences in Google Analytics by taking advantage of user information accessible in Looker, such as in CRM systems or transactional data warehouses.
• The Looker Block for Google Analytics 4 (GA4) expands the solution’s support with out-of-the-box dashboards and pre-baked BigQuery ML models for the newest version of Google Analytics.The Looker Block offers up reports with flexible configuration capabilities to unlock custom insights beyond the standard GA reporting. Customize audience segments, define custom goals to track and share these reports with teams who do not have access to the GA console.

From clinical notes to patient insights at scale

Taking a look at the Healthcare vertical, the Looker Healthcare NLP API Block serves as a critical bridge between existing care systems and applications hosted on Google Cloud providing a managed solution for storing and accessing healthcare data in Google Cloud. The Healthcare NLP API uses natural language models to extract healthcare information from medical text,  rapidly unlocking insights from unstructured medical text and providing medical providers with simplified access to intelligent insights.  Healthcare providers, payers, and pharma companies can quickly understand the context and relationships of medical concepts within the text, such as medications, procedures, conditions, clinical history, and begin to link this to other clinical data sources for downstream AI/ML.   

Specifically, the natural language processing (NLP) Patient View (pictured below) allows you to review a single selected patient of interest, surfacing their clinical notes history over time. It informs clinical diagnosis with family history insights, which is not currently captured in claims, and captures additional procedure coding for revenue cycle purposes.

The dashboard below shows the NLP Term View which allows users to focus on chosen medical terms across the entire patient population in the dataset so they can start to view trends and patterns across groups of patients. 

This data can be used to: 

• Enhance patient matching for clinical trials 
• Identify re-purposed medications
• Drive advancements for research in cancer and rare diseases
• Identify how social determinants of health impact access to care

Managing Costs Across Clouds

Effective cloud cost management is important for reasons beyond cost control — it provides you the ability to reduce waste and predictably forecast both costs and resource needs. Looker’s solution for Cloud Cost Management offers quick access to necessary reporting and clear insights into cloud expenditures and utilization. 

This solution brings together billing data from different cloud providers in a phased approach: get up and running quickly with Blocks optimized for where the data is today (Google Cloud, AWS or Azure) as you work towards more sophisticated analysis for cross-platform planning and even cloud spend optimization with the mapping of tags, labels and cost centers across clouds.

The Looker Cloud Cost Management solution provides operational teams struggling to monitor, understand, and manage the costs and needs associated with their cloud technology with a comprehensive view into what, where and why they are spending money.

Making better decisions with Looker-powered data

Leading companies are discovering ways to get value from all of that data beyond displaying it in a report or a dashboard. They want to enable everyone to make better decisions but that’s only going to happen if everyone can ask questions of the data, and get reliable, correct answers without using outdated or incomplete data and without waiting for it. People and systems need to have data available to them in the way that makes the most sense for them at that moment.  

It’s clear that successful data-driven organizations will lead their respective segments not because they use data to create reports, but because they use it to power data experiences tailored to every part of the business, including employees, customers, operational workflows, products and services.   

As people’s way of experiencing data has evolved, more than ever before, dashboards alone are not enough. You can use data as fuel for data-driven business workflows, and to power digital experiences that improve customer engagement, conversions, and advocacy. 

From Nov. 9 – 11th, Looker is hosting its annual conference JOIN, where we’ll be showing new features, including how we help to:

• Build data experiences at the speed of business
• Accelerate the business value with packaged experiences 
• Unleash more insights for more people in the right way – Deliver data experiences at scale

There is no cost to attend JOIN.  Register here and learn how Looker helps organizations build and deliver custom data-driven experiences that goes beyond just reports and dashboards, scales and grows with your business, allows developers to build innovative data products faster, and ensures data reaches everyone.