Samuel L. Jackson speaking into a microphone in a studio.
The Samuel L. Jackson celebrity voice just got easier to use. Now Alexa users can simply say "Hey Samuel" to ask for jokes, weather, and more. After purchasing the voice, customers can choose whether they want Samuel to use explicit language or not.

Samuel L. Jackson celebrity voice for Alexa gets an update

How Amazon conducted customer-obsessed science research and engineering to release a vastly improved experience.

“Alexa, ask Samuel L. Jackson for the weather.”

Samuel L. Jackson: “It’s cloudy with a chance of me.”

Amazon released the Samuel L. Jackson celebrity voice in December 2019. The new voice allowed Alexa’s customers to get the news, weather, jokes, and more from the legendary actor.

“The Samuel L. Jackson celebrity voice was an important milestone in seeing our multi-persona vision come to life,” says Sai Rupanagudi, senior product manager for the Alexa wake word team.

Sai Rupanagudi
Sai Rupanagudi, Alexa senior product manager

However, while customers enjoyed the interaction with Jackson’s voice, many found the initial experience burdensome.

You have to ask Alexa to ask Samuel everything. I was under the impression I could have Alexa speak to me in Samuel's voice rather than the female voice we currently have. Nope, only if I ask Alexa to ask Samuel. Who wants to add more steps than you already have to take to get a response. I don't get it,” said one reviewer.

Another reviewer said: “While it’s a neat novelty to show friends when they visit...the fact that you have to specifically ask Alexa to ask Sam to do something gets old really fast.”

Rupanagudi and other team members paid close attention to the initial feedback, as did the Alexa text-to-speech team which also addressed customer feedback by further improving the naturalness of Samuel L. Jackson’s voice, so that it more closely matches the lively personality of the actor and producer.

“Customer obsession is central to everything we do at Amazon,” says Remus Mois, senior software development manager within the Alexa text-to-speech team. “We take the feedback of our customers seriously. We decided to improve the Samuel L. Jackson celebrity voice by allowing users to invoke Sam Jackson with a new wake word.”

The concept of multiple personas or voice agents working on the same device is an important milestone for the Voice Interoperability Initiative launched by Amazon last year. The initiative’s principal tenet: different services should work seamlessly alongside one another on a single device, and voice-enabled products should be designed to support multiple simultaneous wake words.

Bollywood star is Amazon's next celebrity voice

Learn more about how customers in India will be able to interact with the iconic voice of Amitabh Bachchan.

“At Alexa, we believe that customers should be able to access their favorite agent or persona directly, be it Alexa, another agent, or a celebrity voice,” says Mois.

The response from beta customers to the new experience was overwhelmingly positive.

“Sam’s voice synthesis is actually amazing, and it no longer feels awkward to invoke him,” said one beta customer. “THANK YOU so much for the custom, and simultaneously active wake word.”

Added another beta user, “It’s great to get Sam’s voice without awkwardly asking ‘Alexa, ask Sam to…’ like I had to before.”

Still another beta user added, “Celebrity voice was fun to use. Wake word was intuitive and easy to use. Enjoyed the personality that comes through with the celebrity voice.”

The task of getting the “Hey Samuel” wake word to coexist with the “Alexa” wake word presented formidable research and engineering challenges. With today’s announcement, Alexa customers can interact with Samuel L. Jackson’s voice directly, simply by saying, “Hey Samuel.”

The research challenges

An interaction with Alexa begins with her name. Only when a device detects Alexa’s wake word does it begin streaming voice data to the cloud.

Shiv Vitaladevuni
Shiv Vitaladevuni, Alexa senior machine learning manager

Developing machine-learning models for the new “Hey Samuel” wake word is one of the more challenging problems Shiv Vitaladevuni and his team have encountered since he joined the Alexa organization in 2013. Vitaladevuni, an Alexa senior machine learning manager, leads the wake word team.

“The Alexa wake word has billions of interactions every week,” says Vitaladevuni. “However, there was a paucity of training data for the ‘Hey Samuel’ wake word. To develop a multi-wake-word model for ‘Hey Samuel’ and Alexa, we had to develop new training and data modeling techniques, while drawing on learnings from the past.”

However, drawing from this past experience came with its own unique set of challenges. Researchers had to train the algorithm to recognize the new wake word (“Hey Samuel”), while also concurrently detecting the other primary wake words – “Alexa”, “Echo”, “Amazon”, and “Computer”.

Instead of training a model for each wake word separately, Alexa’s scientists leveraged multi-target learning, where multiple learning tasks are carried out concurrently by leaning on similarities across tasks. In multi-target learning, one input is used to predict multiple outputs. By its very nature, multi-target training is inherently more complex, given the large number of variables, and the speeds at which they must be processed.

“Multi-target training isn’t an easy task,” says Vitaladevuni, “especially when you are contending with wake words that are a single word (“Alexa”, “Amazon”, “Echo” and “Computer”) and a phrase (“Hey Samuel”). The team had to innovate in a number of areas to solve for this problem. To give just one example, we had to conduct extensive research on developing new data preparation and training techniques to balance the data sets for each word. We have made significant progress in the difficult task of ensuring multi-target training performs with the same accuracy we expect from our devices, and we are continually working to improve."

How to add Samuel L. Jackson's voice to your echo

The team also had to innovate to deal with the issue of false rejects. A false reject refers to an instance where a customer says “Hey Samuel” or “Alexa”, but the wake word goes unrecognized. With no audio sent to the cloud, the team doesn’t have any data to help reduce false rejects.

To get around this obstacle, Alexa’s scientists utilized transfer learning techniques to train their new multi-wake word model to accept a wide spectrum of nuances in pronunciations, thereby reducing false rejects. Transfer learning allows the algorithm to take skills learned on one domain and transfer the learnings to another domain. In this instance, the team trained a baseline model on a medium vocabulary recognition task and then adapted the model to recognize the “Hey Samuel” wake word more efficiently, utilizing minimal amounts of training data.

The engineering challenges


The wake word detector, unlike Alexa’s other machine learning systems, must run on-device. This on-device computing resource is far more limited than what’s available in the cloud for Alexa’s other components.

We’re excited to see how customers respond to this updated experience, and how we will continue to improve the experience for our customers.
Sai Rupanagudi

As a result, Alexa scientists and engineers had to develop wake word solutions that could carry out the complex task of detecting two wake words without exceeding CPU, memory and other resources. To complicate matters, the multi-wake word functionality must run on both old and newer Echo devices.

Amazon’s engineering team also developed inference algorithms that are able to adjust to varying prefixes and their corresponding lengths for wake words that might be used in the future. This will be particularly useful as additional partner agents and personas come online with different lengths and prefixes, and will allow the team to stay true to its vision outlined in the Voice Interoperability Initiative.

While the updated Samuel L. Jackson skill has been released today, it’s still Day One for the wake word team. Now that the team has added one new wake word, it is continuing to break ground in research related to how to add new wake words to a multi-target model, using minimal training data, and without degrading the accuracy of existing wake words.

“With this new ability to develop wake words with little to no prior data, we have the opportunity to support much richer customer experiences on Alexa-enabled devices,” says Rupanagudi. “We’re excited to see how customers respond to this updated experience, and how we will continue to improve the experience for our customers.”

Research areas

Related content

  • Staff writer
    December 24, 2024
    Large language models remained a hot topic, but posts about cryptography and automated reasoning also drew readers.
  • Staff writer
    December 24, 2024
    From cloud databases and anomaly detection on graphs to recession prediction and Amazon's new Nova foundation models, these are the most viewed publications authored by Amazon scientists and collaborators in 2024.
  • Staff writer
    November 14, 2024
    Large language models predominate, both as a research subject themselves and as tools for researching topics of particular interest to Amazon, such as speech, recommendations, and information retrieval.
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
US, WA, Bellevue
mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in optimization and machine learning to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and airplanes to transport millions of packages and other freight between warehouses, vendor facilities, and customers, on time and at low cost. The Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative optimization and machine learning models to improve driver routing and procurement efficiency. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on optimization and machine learning. You will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities - Design and develop optimization and machine learning models to inform our hardest planning decisions. - Implement models and algorithms in Amazon's production software. - Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems. - Lead complex modeling and data analyses to aid management in making key business decisions and set new policies. - Write documentation for scientific and business audiences. About the team This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We leverage technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges. Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
US, CA, Palo Alto
Amazon’s Advertising Technology team builds the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. In this organization you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading companies. Amazon Publisher Services (APS) helps publishers of all sizes and on all channels better monetize their content through effective advertising. APS unites publishers with advertisers across devices and media channels. We work with Amazon teams across the globe to solve complex problems for our customers. The end results are Amazon products that let publishers focus on what they do best - publishing. The APS Publisher Products Engineering team is responsible for building cloud-based advertising technology services that help Web, Mobile, Streaming TV broadcasters and Audio publishers grow their business. The engineering team focuses on unlocking our ad tech on the most impactful Desktop, mobile and Connected TV devices in the home, bringing real-time capabilities to this medium for the first time. As a successful Data Scientist in our team, · You are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, and can credibly interface between technical teams and business stakeholders. You will collaborate directly with product managers, BIEs and our data infra team. · You will analyze large amounts of business data, automate and scale the analysis, and develop metrics (e.g., user recognition, ROAS, Share of Wallet) that will enable us to continually measure the impact of our initiatives and refine the product strategy. · Your analytical abilities, business understanding, and technical aptitude will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. · You will have direct exposure to senior leadership as we communicate results and provide scientific guidance to the business. Major responsibilities include: · Utilizing code (Apache, Spark, Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems. · Collaborate with product, BIEs, software developers, and business leaders to define product requirements and provide analytical support · Build customer-facing reporting to provide insights and metrics which track system performance · Influence the product strategy directly through your analytical insights · Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
IL, Tel Aviv
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. Key job responsibilities PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience 3+ years of building models for business application experience Experience in patents or publications at top-tier peer-reviewed conferences or journals Experience programming in Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
IL, Haifa
Come join the AWS Agentic AI science team in building the next generation models for intelligent automation. AWS, the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems that will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, API orchestration, Planning, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making.
US, NY, New York
Join us in a historic endeavor to make Generative AI accessible to the world with breakthrough research! The AWS AI team has a world-leading team of researchers and academics, and we are looking for world-class colleagues to join us and make the AI revolution happen. Our team of scientists drives the innovation that enables external and internal SageMaker customers to train their next generation models on both GPU and Trainium instances. As part of the team, we expect that you will develop innovative solutions to hard problems, and publish your findings at peer reviewed conferences and workshops. AWS is the world-leading provider of cloud services, has fostered the creation and growth of countless new businesses, and is a positive force for good. Our customers bring problems which will give Applied Scientists like you endless opportunities to see your research have a positive and immediate impact in the world. You will have the opportunity to partner with technology and business teams to solve real-world problems, have access to virtually endless data and computational resources, and to world-class engineers and developers that can help bring your ideas into the world. About the team Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist in the Content Understanding Team, you will lead the end-to-end research and deployment of video and multi-modal models applied to a variety of downstream applications. More specifically, you will: - Work backwards from customer problems to research and design scientific approaches for solving them - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals About the team Our Prime Video Content Understanding team builds holistic media representations (e.g. descriptions of scenes, semantic embeddings) and apply them to new customer experiences supply chain problems. Our technology spans the entire Prime Video catalogue globally, and we enable instant recaps, skip intro timing, ad placement, search, and content moderation.