Oracle on Tuesday unveiled a spate of new capabilities for its HeatWave database aimed at better enabling customers to develop generative AI capabilities in Oracle Cloud Infrastructure.
New features — among many others — include batch processing for using large language models (LLMs) to respond to user queries and automatic vector store updating in HeatWave GenAI, the addition of bulk ingest capabilities to HeatWave MySQL, and the ability to store and process larger models in HeatWave AutoML.
Together, the new HeatWave features address critical needs as enterprise interest in developing AI models and applications, including generative AI, continues to increase, according to Holger Mueller, an analyst at Constellation Research.
This release is all about making it easier for developers to use vector capabilities inside HeatWave. Basically, Oracle needs to make sure that the data content in HeatWave is available and it is easy for developers to use the vector support. If [Oracle] succeeds, the future of HeatWave in the AI era is set. Holger MuellerAnalyst, Constellation Research
Each, like the new HeatWave features, focuses on better enabling customers to use AI as part of the decision-making process. Similarly, new integrations with Informatica and Microsoft Azure address generative AI development.
The new capabilities were revealed during Oracle CloudWorld, the vendor’s user conference in Las Vegas.
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Based in Austin, Texas, Oracle is a tech giant that provides a broad spectrum of data management and analytics capabilities, including a variety of database options.
HeatWave GenAI was first launched in June, while recent platform updates include adding vector search to Oracle Database 23ai in May and the July unveiling of Exascale, a new architecture for the cloud that will become the Oracle Database infrastructure.
Heating up
HeatWave is a MySQL database that that allows customers to query and analyze data within the database environment so that they don’t have to extract, transform and load data before using it to inform decisions.
Competing platforms include Amazon Redshift, Databricks, Google BigQuery, Snowflake and Teradata.
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HeatWave GenAI is a feature within HeatWave and is designed to enable users to build AI models and applications using the data stored in the database. Capabilities included when the feature was initially launched were in-database LLMs, automated in-database vector storage, scalable vector search and HeatWave Chat, an AI-powered assistant that enables users to have natural language interactions with data.
LLM inference batch processing aims to help developers improve application throughput by executing multiple requests simultaneously, rather than just one at a time. Automatic vector store updating, meanwhile, provides AI application developers with the most current data available by automatically updating object storage.
More new HeatWave GenAI features include multilingual support so that similarity searches can be performed on documents in any of 27 languages when developing applications, support for optimal character recognition so developers can include scanned content saved as images when training applications, and JavaScript support to more easily let users build AI chatbots.
Like Mueller, Shawn Rogers, an analyst at BARC US, noted that the new HeatWave GenAI features add significant value because they help simplify developing AI models and applications.
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“Heatwave GenAI enables customers to de-risk AI-driven projects through a highly integrated service that removes much of the complexity surrounding creating AI applications,” he said. “Built-in LLMs and easy vector store creation help customers avoid do-it-yourself pitfalls without [requiring] extensive AI skill sets.”
In particular, automated vector store updating is a significant addition, Rogers continued, calling it “an excellent feature in Heatwave.”
Beyond HeatWave GenAI, Oracle updated numerous other HeatWave database features. Highlights include the updates to HeatWave Lakehouse and AutoML, according to Mueller.
New HeatWave Lakehouse capabilities include the ability to write results to object storage so that users can more easily and cost efficiently share and store query results. Also included is automatic change propagation to ensure that users always have access to the most up-to-date data.
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New HeatWave AutoML features include increasing capacity so users can train larger machine learning models than was previously possible, data drift detection so developers can know when models need to be retrained, and topic modeling that enables users to more easily discover insights in their text data.
“HeatWave Lakehouse is critical,” Rogers said. “[It enables users] to combine HeatWave and lakehouse data, which is key because enterprises need to rely on lakehouses for insights, and even more with AI. And the HeatWave AutoML [update] is very important to keep down the cost of a more powerful — but therefore also more complex — database.”
In addition to new HeatWave capabilities, Oracle revealed that a free version of the database is now available in the Oracle Cloud Infrastructure (OCI) Always Free Service, enabling organizations to get started with the database by developing and running small applications at no cost.
Enterprises might realize these seven benefits when using generative AI.
Other new capabilities
Oracle’s HeatWave updates, many designed to better enable developers to build AI models and applications, are just one aspect of the tech giant’s push to improve the AI development experience for its customers.
Another development is its plan to develop and deliver Oracle Intelligent Data Lake as a foundational part of the Oracle Data Intelligence Platform.
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Oracle expects Intelligent Data Lake to be available on a limited basis at some point in 2025. Once available, its aim will be to combine data orchestration, warehousing, analytics and AI in a unified environment powered by the OCI to more easily enable customers to use data from diverse sources.
Data is growing at an exponential rate. So is the complexity of data and the number of sources from which data is collected. Tools that address that volume and complexity with more advanced capabilities than those built to handle the lower data volumes and more simplistic data of the past are the appropriate next step for vendors such as Oracle, according to Rogers,
“The upcoming addition of Oracle Intelligent Data Lake is a logical step forward for the company,” he said. “Nearly all enterprise customers have a highly diverse data ecosystem, and the integration of Oracle’s data intelligence platform and OCI clearly provides additional flexibility and function. Customers optimizing their architecture to take advantage of AI will also benefit.”
Specific features of Oracle Intelligent Data Lake include generative AI-powered experiences to enable conversational data analysis and code generation, integration capabilities that enable users to combine structured and unstructured data, a data catalog, Apache Spark and Apache Flink for data processing and native integrations with other Oracle platforms, as well as with open source tools.
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Like the pending development of Intelligent Data Lake, new AI-powered applications in Fusion Data Intelligence now in preview are aimed at helping Oracle customers derive greater value from their data.
Like many data platform vendors, including Databricks and Snowflake, Oracle has made it a priority to provide users with prebuilt applications specific to individual industries to streamline exploration and analysis.
Now, the tech giant plans to infuse Oracle Cloud Human Capital Management (HCM) and Oracle Cloud Supply Chain Management (SCM) with AI capabilities to further improve the time it takes to reach insights in what Rogers called a “meaningful way.”
A new tool in HCM called People Leader Workbench is designed to help organizations achieve business goals by adapting their talent strategy to changing business needs. Meanwhile, a new tool in SCM called the Supply Chain Command Center aims to provide recommendations that better enable organizations to quickly respond to changing supply, demand and market conditions.
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“Many companies have long found the time gap between insight and action challenging,” Rogers said. “Fusion Data Intelligence … helps Oracle clients close that gap in a meaningful way. Intelligent AI-powered applications are critical for companies looking to deploy AI in business systems for faster, accurate and actionable insights.”
Finally, GenDev is intended to provide customers with a cohesive environment for generative AI application development by combining previously disparate tools in Oracle Database 23ai and adding new features.
Among the new features are support for more LLMs including integrations with Google Gemini and Anthropic Claude, improved retrieval-augmented generation (RAG) capabilities, access to Nvidia GPUs and synthetic data creation.
Next steps
With Oracle focusing intently on providing customers with the capabilities to develop and deploy generative AI models and applications, Mueller said it’s important that Oracle do so for not only customers deploying on Oracle’s own cloud, but also users of other clouds.
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Many large enterprises use different clouds for different operations. In addition, they still keep some data on premises and in private clouds. Therefore, as Oracle scales out its generative AI development capabilities, it needs to do so for users of any cloud infrastructure.
“[Oracle needs to] make sure [deployment] is the same across Azure, Google and more clouds,” Mueller said. “[They need to] provide multi-cloud management tools, dig deeper in functionality. … Whatever the most popular use cases are, Oracle needs adoption.”
Cloud computing costs were higher than many enterprises expected even before the surging interest in generative AI over the past two years. Now, vital functions such as vector search and storage, developing and running RAG pipelines and deploying LLMs are adding new workloads and their corresponding costs.
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“Cost control and transparency must be at the forefront of Oracle’s strategy as it continues to add to and integrate its technologies with AI,” Rogers said. “Enabling a wider community of users to leverage AI will require simple cost controls to deliver value.”
Eric Avidon is a senior news writer for TechTarget Editorial and a journalist with more than 25 years of experience. He covers analytics and data management.
It is a watershed moment in the history of the U.S. nuclear industry. Constellation Energy plans to restart the Three Mile Island nuclear plant , with operations slated to resume in 2028 subject to approval by the Nuclear Regulatory Commission. Its stock has surged nearly 20% on the news. The deep pockets of Microsoft will breathe new life into the plant. The tech company signed a 20-year agreement to purchase clean power from the plant to offset emissions from its artificial intelligence data centers. The Three Mile Island restart is not just a milestone for Constellation. It demonstrates the growing financial opportunity that nuclear power represents for utilities and their investors. Only one power sector stock is hotter than Constellation right now. Vistra Corp. shares surged more than 14% after the Three Mile Island announcement Friday. VST YTD mountain Vistra shares, YTD The power company, headquartered outside Dallas, is viewed as one of the lead contenders to ink a data center nuclear deal next. Vistra leads the market Previously an obscure name, Vistra shares have soared more than 175% this year, blowing past the AI chip powerhouse Nvidia to lead the entire S & P 500 on its data center opportunity. Vistra completed the acquisition in March of two nuclear plants in Ohio and one in Pennsylvania through its $3.4 billion purchase of Energy Harbor . The broader utilities sector has gained about 25% this year, in large part due to the data center demand trend. Investors can play this trend through buying independent power producers like Vistra, rather than regulated utilities, because they dispatch power based on economics, according to Shahriar Pourreza, senior managing director of North American power and utilities at Guggenheim Securities. Jefferies initiated coverage of Vistra earlier this month with a buy rating, choosing the company as its best-in-class stock in the power sector. Wall Street analysts have an average stock price target of $116.89 per share, implying 26% upside from Thursday’s close of $92.52, according to FactSet data. VST NVDA YTD line Vistra vs. Nvidia “Vistra’s years of acquisitions, rationalizations, and lessons learned about risk have positioned the company well for the power markets of today,” Jefferies analysts led by Julien Dumoulin-Smith told clients in a note earlier this month. “Vistra’s timely acquisition of nuclear portfolio Energy Harbor in 2023 gives the company a coveted nuclear portfolio,” the analysts said. Vistra CEO Jim Burke told investors that the company is having numerous conversations with customers about directly powering data centers with its plants and is “in due diligence for a number of sites.” Burke specifically called out Comanche Peak, a twin reactor nuclear plant with 2.4 gigawatts of capacity outside Forth Worth, Texas. “We’re seeing some interest in Comanche Peak,” Burke told analysts on the company’s second-quarter earnings call in August. Other power companies poised to benefit from the growing nuclear demand from data centers include NextEra Energy and Dominion Energy . NextEra CEO John Ketchum told investors in July that the company is considering restarting the Duane Arnold nuclear plant in Iowa “There would be opportunities and a lot of demand from the market if we were able to do something with Duane Arnold,” Ketchum said on NextEra’s second-quarter earnings call. NextEra was up just 1.4% on Friday, but has gained 37% so far this year. The power company has the equivalent of a buy rating from 62% of Wall Street analysts, though its stock has largely caught up with the Street’s average price target of $83.94 per share, according to FactSet. Dominion Energy CEO Robert Blue told investors that the utility would consider locating a data center next to the Millstone nuclear plant in Waterford, Connecticut. Dominion has gained more than 22% this year, though nearly 80% of Wall Street analysts have put a hold on its stock for now.
This is the world’s most powerful Mini PC and I can’t wait to test it: Beelink’s tiny computer packs the Ryzen AI 9 HX 370 CPU and promises to deliver the GPU performance of an RTX 3050 with a whopping 50 TOPS
Chinese manufacturer Beelink has earned a reputation for producing quality mini PCs across a range of price points. The Beelink U59 is a definite standout for those looking for a budget option – in our four and a half star review we said it offered a “good feature set that might appeal to many different customers.”
Beelink also offers higher-end products like the GTi Ultra, which features Intel‘s 12th to 14th Gen Core CPUs, with support for Beelink’s exclusive eGPU solution for users requiring extra graphics power. Beelink has been developing its SER series for some time. Its most recent release was the SER8 model powered by an AMD Ryzen 7 8845HS Hawk Point processor, 32GB of DDR5 memory, and 1TB of storage. Priced around $650, the SER8 delivered strong performance in a compact design.
Coming up next is the SER9, the first mini PC to feature AMD‘s Ryzen AI 9 HX 370 Strix Point CPU, paired with AMD Radeon 890M graphics. The Strix Point processor includes four Zen 5 cores, eight Zen 5c cores, and AMD’s latest RDNA 3.5 Radeon 890M integrated graphics. It also incorporates a Ryzen NPU capable of up to 50 TOPS of AI performance, making it ideal for AI-driven tasks. If you need extra AI functionality, the SER9 includes a built-in MIC AI chip for seamless voice recognition.
Ports galore
Design-wise, the SER9 closely mirrors its predecessor, the SER8, as well as the GTi Ultra. Although we haven’t had any confirmation, is expected to come with 32GB of LPDDR5x-7500MHz memory and an M.2 slot for PCIe 4.0 SSD storage. According to information leaked on Weibo, the mini PC will be available in four colors: Frost Silver, Flame Orange, Pine Green, and Deep Gray.
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As with many mini PCs, the Beelink SER9 offers a wide range of ports. It includes a USB4 Type-C port (40 Gbps), a USB 3.2 Gen 2 Type-C port (10 Gbps), two USB 3.2 Gen 2 Type-A ports (10 Gbps), two USB 2.0 Type-A ports (480 Mbps), an HDMI 2.0 port, and a DisplayPort 1.4. There’s also a 2.5 GbE Ethernet port, with two 3.5mm audio jacks for microphones and speakers. This model also includes integrated speakers.
Beelink has stated that the SER9 will be priced at $999, with shipping expected to begin in October. While initially announced for the Chinese market, the mini PC is anticipated to be available globally (eventually) through Beelink.com.
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This time of the year always excites us: it brings a look at what’s new in iPhone photography. First up is our brief look at the technical specifications of the new iPhone 14 Pro cameras. Our next post field tests the new cameras and their output. Whether you are a first-time reader or a long time listener, we promise an exciting few weeks.
iPhone 13 Pro vs. iPhone 14 Pro
We expect the iPhone 14 to have the same camera system as the iPhone 13 Pro, minus its telephoto camera, so we’ll keep this post limited to the iPhone 14’s Pro version, which has the most major camera changes. Fortunately, the the iPhone 14 Pro and Pro Max have the same camera array, which keeps things simple. With the help of a Halide Technical Readout sent to us, it’s straightforward to analyze the year over year hardware changes. But first, a disclaimer…
Huge breakthroughs today are just as much about software as hardware. Sure, software can’t replace a giant large telephoto zoom lens (yet), but it allows for breakthroughs in dynamic range, exposure, night photography, adding nice blurred backgrounds, and much more. When it comes to computational photography, the quality of your software and processing power plays as important a role as the physical camera itself. It’s silly to judge the new iPhone entirely on sensor specs, and we can’t wait to run full package through its paces as soon as it arrives at Halide HQ.
iPhone 14 Pro Technical Readout Comparison
Without further ado, here’s a side by side comparison with the iPhone 13 Pro to iPhone 14 Pro. Specs changes are marked in bold:
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Wide
The Wide camera sees the greatest changes. The lens gets a bit wider, a 2mm focal length difference. The aperture is smaller (‘slower’), means the lens collects less light. This was probably necessary to work with a larger sensor. We calculate that the Wide camera is able to collect 20% more light compared to last year’s camera, even with this slightly worse aperture, thanks to its larger size.
We’re astonished by the improvement in the camera sensor’s ISO range. It goes far beyond previous iPhone cameras. Given high ISO values are accompanied by more noise, it’s highly likely this ISO range is made possible by how its higher resolution sensor combines 4 pixels into one, vastly reducing noise.
Apple refers to this as ‘quad-pixel’, and for almost all apps, it is how the camera will operate. By default, camera apps will ‘see’ the new Wide camera as if it were a 12 megapixel camera. Behind the scenes, iOS will downsize those 48 megapixels, combining four pixels into one, reducing noise. This will avoid breaking third-party apps, which probably aren’t ready for those larger images that require 4x the memory.
It does mean that if you were hoping to shoot 48 megapixel JPGs, you are likely out of luck without a third party camera app. With the first-party camera app, you can only capture 48 megapixel images by shooting in ProRAW. We hope this was a product choice as opposed to a technical limitation, and they leave more options available to third-party developers.
We look forward to testing the sensor in low-light: its high ISO range, quad-pixel shooting and claimed ‘second generation’ sensor-shift stabilization, we are expecting a big leap in image quality in at night.
Finally, we noticed that minimum focus distance — which is the closest the camera will focus on objects — has taken a step back, going from 150mm (5.9 inches) to 200mm (7.8 inches). While two inches doesn’t seem like much, if you were frustrated by your iPhone 13 switching between the ultra-wide (‘macro’) lens and regular camera, it’s possible this could happen a little more often new iPhone. The new lens design just can’t focus as close as the 13 Pro’s. We’ll be interested in seeing how much they’ve mitigated this in software.
Telephoto
The telephoto camera might be our team’s favorite, and it sees a fairly small spec bump. Apple has been fairly mum about this camera, only calling it ‘improved’. They might just mean that it benefits from the new Photonic Engine software pipeline, but the improved ISO range gives us hope they upgraded the sensor.
Ultra-Wide
With iPhone 13 Pro, Apple got serious about the image quality on its Ultra-Wide camera. This year, we’re seeing another sensor size bump; its larger pixels and area offset a slightly slower aperture. However, it lost a slight touch of its ultra-wideness, moving to a 14mm focal length (full frame equivalent).
Across the board, we are seeing what should be solid low-light improvements. A larger sensor and higher ISO sensitivity should allow this camera to further mature to be a good option for high-quality images. Apple actually claimed the greatest improvements to this camera in its keynote, claiming ‘up to 3×’ better images. We will have to see what that entails in testing.
Front-facing
Apple made a big change to the front of the iPhone this year. The Dynamic Island features the TrueDepth hardware we’ve come to love; a host of IR projector/sensor hardware to enable Face ID and a regular old front-facing (or ‘selfie’) camera. Despite being shrunk into a little isle, the front-facing camera got an upgrade.
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A big change here is the front-facing camera gaining variable focus (and autofocus) for the first time since the very first iPhone. In addition, a nice improvement in aperture should allow a bit more depth of field and light to reach this little camera. We’ll have to see how much of a difference or need there is for autofocus; if the sensor is indeed larger this year, it might allow for sharper shots.
What remained the same
We haven’t been able to confirm many changes in the telephoto and LIDAR systems on the iPhone 14 Pro. Despite this, we are seeing signs that point to an all-new telephoto camera sensor. The LIDAR system has changed slightly, throwing a wider grid of dots that corresponds with the new, wider 24mm focal length of the Wide camera. Otherwise, it appears unchanged, and so does the TrueDepth depth-sensing infrared hardware despite its miniaturization.
Stay tuned
As is tradition, we are going to test the iPhone 14 Pro’s camera system deeply — planning several outings in Mexico and the desert Southwest. We’ll be testing 48 megapixel shooting, RAW performance, quad-pixel ins and outs and extensively inspecting the new Photonic Engine. We will also be checking out the new iPhone 14’s camera. In the mean time, check out Austin Mann’s excellent iPhone 14 Pro camera review.
You can follow us on Twitter or Instagram to read about our findings in the meantime.
What sets humans apart from the rest of life, or indeed inert matter? Many people would respond that it is our intelligence. Yet the rise of seemingly intelligent machines challenges this way of thinking. The companies behind these new artificial intelligence technologies, in the form of ChatGPT and its rivals, speak of achieving artificial general intelligence – machines that have the same level of intelligence as humans across a range of tasks.
Does this meteoric rise in AI make human intelligence, and therefore us, less special? Neil Lawrence, professor of machine learning at the University of Cambridge, doesn’t think so. In fact, he thinks we should throw out the concept of artificial general intelligence altogether.
In his new book The Atomic Human: Understanding ourselves in the age of AI, Lawrence makes the case that it is only by better understanding our own intelligence, and how wildly different it is to its artificial counterpart, that we can make the most of both. Here he tells New Scientist why he thinks both human and artificial intelligence are misunderstood, why it is pointless to compare the two and why, ultimately, we need a more nuanced understanding of intelligence.
Alex Wilkins: What do you make of the trend to compare artificial to human intelligence?
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Neil Lawrence: Most of these arguments are pointless, they are irrelevant. Of course, the nature of the intelligence that we’re seeing in AI is extremely different from our own. It’s absurd that people are talking about this intelligence as if it’s anything to do with us.…
With ChatGPT taking the internet by storm, technology is front of mind for both consumers and brands. Consumers are excited about new developments in the virtual space, and are eager to test AI tools and products out themselves, while brands are seeking ways to apply new Artificial intelligence (AI) tech in order to grow their businesses. In this blog we explore how AI technology is changing consumer search habits online, and what impact it will have on consumer behaviour.
Brands need to adapt as Generation Z shifts search behaviour to social media
While search engines may continue to dominate, the younger generations are increasingly making use of alternative ways to search for information. This is most evident when it comes to clothes, as nearly half of Gen Z are most likely to turn to social media when searching for outfit ideas, while one in three would turn first to social media for gift ideas.
One advantage of using social media sites such as TikTok for search is its ability to provide video content, with personal recommendations, rather than just links to websites. The video-based responses provided by platforms, such as TikTok and Instagram, can offer a more immersive and engaging response than search engines. It can also offer more ‘personal’ recommendations by others who have uploaded reviews and content. In the context of fashion, vibrant tryout videos will be of more appeal to people who are looking to see how different fashion items fit together, or not, hence providing more useful information for the consumer instead of the usual bland, static images.
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TikTok personality james_edward posts fashion videos of him trying out different styles of outfits in a creative, easy to follow manner. Source: TikTok, @james_edward
TikTok has recognised its users wanting to use the site in this way and is seeking to monetise it. For example, the platform has been testing features that identify keywords in comments and links to search results for them. Although the platform has recently become embroiled in controversy in the US, its business model and formula is likely to be ingrained in Gen Z creators, advertisers and audience, and consumers are getting more used to finding advertising content that engages them and speaks to their needs.
Search engines fight back with AI enhancements
As social media platforms gain increasing popularity as de facto search engines, the old guard are fighting back, with AI rapidly improving search results in search engines. With the explosion of ChatGPT, conversational AI could take this even further, with both Bing and Google exploring how the technology can provide a more personalised and nuanced search result than simply offering a list of hyperlinks to relevant websites. Improvements in natural language processing (NLP) models will enhance performance in voice searches, thus also enhancing the accessibility of internet usage.
Tech giant Google has been seeking ways to make search more ‘immersive’. Using AI, the search engine can now recommend specific parts of a video that could be relevant to a search. Google Maps already features an augmented reality version that uses the camera of a phone to overlay search information on an image of the surrounding area.
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Google is implementing new AI technologies in its suite of services, including new AR functions in its signature search engine. Source: Google
Microsoft, on the other hand, is integrating OpenAI into its Edge browser and new Bing search engine with features similar to ChatGPT. Features include a Bing Chat function which transforms search data into a full interactive human-like conversation. This new launch by Microsoft could encourage some consumers to the browser and alter the search market share.
AI poses challenges, but brands and consumers will benefit in the long run
AI has already improved and transformed the search experience behind the scenes, but the introduction of more conversational text based answers could herald a new era of search. The idea of AI and having ‘conversations’ with computers can divide consumers. While some think it’s exciting as AI could make life easier, others worry about the reliability of the information, and what happens when AI content becomes so widespread online, that AI search engines are generating answers based on AI generated content.
For brands, the integration of AI will provide an opportunity to create a new and exciting way to engage with consumers. For example, brands may need to rethink how they create an online presence so that Generative AI search talks favourably about them, or recommends them in the right instances. However, Generative AI will also create significant opportunities for the experience within a brand’s site. For example, Shopify has announced plans to add a new search function to its app in 2023, leveraging ChatGPT’s technology.
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OpenAI announced that ChatGPT and Whisper models are now available on their API, giving developers access to cutting-edge language and speech-to-text capabilities; Shopify is one of the brands that uses this AI-technology extensively to help consumers find the right products. Source: OpenAI
What we think
Advances in AI technology will continue to influence consumers and brands as they seek to harness the power of the internet and social media. The integration of conversational AI into search engines will transform the way consumers look for information and discover brands and products. As search becomes more immersive and conversational it will change the way brands need to position themselves online to ensure they remain visible and stand out from the myriad of content.
Brands need to be aware that the way consumers search for information is changing. Search engine optimisation is just one aspect of an increasingly fragmented online journey. Social media activity shouldn’t just be viewed as a way to drive traffic to a website or generate buzz around a brand, but it should be viewed as an opportunity to help consumers find what they are looking for and even buy directly via the platform.
Generative AI has the potential to transform the way consumers engage with brands and search for information. Gen Z will be first to embrace this technology, and will expect a more personalised and conversational relationship with brands than ever before.
Blood Line: A Rebel Moon Game | Official Announcement Trailer | Netflix
The Rebel Moon series is continuing at Netflix, although the most recent announcement isn’t for another movie. The streaming service announced Blood Line: A Rebel Moon Game, a standalone action video game set in director Zack Snyder’s Rebel Moon space opera-verse, during its Geeked Week event on Thursday.
Blood Line is a top-down action game akin to Diablo 4 from Super Evil Megacorp, most recently known for the roguelike Teenage Mutant Ninja Turtles: Splintered Fate. It lets players team up online to take down hordes of enemies. You can check out a little of the gameplay in the trailer above. Like other Netflix titles, this will only be available on mobile and only to Netflix subscribers through its app. You can sign up for the beta now.
The core gameplay involves choosing between four classes based on characters similar to the ones you meet in the movies: Bannerguard, Evoker, Kindred, and Forsaken. The Bannerguard is your high-damage tank, while Kindred is long-range. The Forsaken are for players who are fans of dealing damage with dual-wielding weapons. Finally, the Evoker is the healer and support character.
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Netflix writes that each will have “unique backstories” and “specific Motherworld-vanquishing motivations” that will mirror what you’ll get with the characters watching the movies. The game will be live service, although because it’s available for free through a Netflix subscription, the updates will be in the form of narrative chapters that expand the story and help you build up a rebellion.
“And then when updates come in, it’s not just, ‘Oh, this one is always better,’ but it’s a new kind of piece to your puzzle and how you want to mix them up so they won’t just be the next thing that’s bigger and stronger, but it’ll actually be a different spice, as it were, to put into your recipes of your loadout,” Super Evil Megacorp design director Robert Gallerani said in a press briefing attended by Variety.
Super Evil Megacorp announced its partnership with Netflix in 2023, noting that it had been working with the media company on “an amazing new IP” that would allow it to be a “transmedia pioneer.” “We love building worlds, and with Netflix, we get the opportunity to be part of building a universe far larger than a single game – and we will build it simultaneously with the rest of the IP universe,” a spokesperson from the developer wrote.
While the first Rebel Moon did poorly with critics, including Digital Trends, Netflix reported it was the most-viewed title on the service within its first week of release with 29.3 million views. Later, Snyder claimed that it “probably” surpassed the number of people who saw Barbie in theaters. Netflix has since released the sequel, along with a director’s cut with extra scenes.
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