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Informatica update targets preparing data for AI development

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Informatica update targets preparing data for AI development

Informatica on Wednesday unveiled its Fall 2024 Release featuring new tools aimed at enabling customers to prepare data for training AI models and applications, including improved data integration capabilities.

Data is the foundation of any AI model or application, providing the AI tool with the intelligence it needs to inform decisions and take actions. The data, however, must be prepared properly for the model or application to be effective.

With poorly prepared data such inaccurate or irrelevant information, the AI tool will deliver incorrect outputs. But with well-prepared, high-quality data, while accuracy is not guaranteed, the likelihood of AI models and applications delivering inaccurate outputs greatly decreases.

Ensuring that data is properly prepared before using it to train AI models and applications is therefore vital, according to Stephen Catanzano, an analyst at TechTarget’s Enterprise Strategy Group.

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“Data readiness for AI is critical since the outputs from AI are only as good as the data it is trained on,” he said. “If you train AI on data that says the world is flat, that is what it will believe.”

Proper data preparation for AI includes building trusted data sources with top data quality including accurate, reliable, contextual, governed, current and diverse data, Catanzano continued.

“This is the most crucial step in the process of building a generative AI solution using enterprise data along with the data platform infrastructure to support it,” he said.

Kevin Petrie, an analyst at BARC U.S., likewise noted that proper data preparation is a crucial part of AI development. Without governance measures that result in trustworthy data, models and applications won’t succeed.

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“We’ve reached the stage in this latest AI innovation cycle in which early adopters realize that, to achieve meaningful production deployments, they need to get serious about data governance,” Petrie said. “Powerful models will fail without trusted inputs by making incorrect inferences, generating false or toxic content, and so on.”

Based in Redwood City, Calif., Informatica is a data management specialist whose platform, the Intelligent Data Management Cloud (IDMC), enables customers to integrate and prepare data for analysis.

In May, the vendor launched Claire GPT, a generative AI-powered assistant that lets customers use natural language rather than code to work with data, and a low-code/no-code environment for developing generative AI tools. A month earlier, the vendor was a rumored acquisition target of Salesforce before talks fell through amid dissatisfaction from investors.

New capabilities

Fueled by OpenAI’s launch of ChatGPT in November 2022, which was a significant improvement in generative AI capabilities, enterprise interest in developing both traditional AI as well as generative AI tools has surged over the past two years.

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Because large language models (LLMs) such as ChatGPT and Google Gemini enable true natural language processing, enterprises are aiming to combine their proprietary data with LLM capabilities to enable their employees to work with data using natural language rather than code. With coding skills no longer always needed to work with data, more employees within organizations can use analytics to inform decisions, making decision-making more efficient and accurate.

In addition, because LLMs can be trained with proprietary data to automate repetitive tasks that take up a significant amount of data experts’ time, AI tools can make application developers, data engineers, data scientists and other trained experts more efficient.

However, if the proprietary data used to train AI tools isn’t prepared properly, the models and applications trained on that data won’t perform as intended.

Enterprises often possess massive amounts of data, much of it unstructured such as text, images and audio files that have been loaded into a data lake or some other storage repository and left untouched. Even some structured data such as financial and point-of-sale transaction records is often simply loaded into a data warehouse and left alone.

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To get all that data ready to inform AI tools, it needs to properly prepared, according to Gaurav Pathak, Informatica’s vice president of product management AI and metadata.

“Many organizations hold terabytes or petabytes of data, both structured and unstructured. But too much of that data has not been properly managed and governed — it’s not what we call AI ready,” he said. “Cleaning up messy data will help enterprises prepare data for AI.”

Informatica’s Fall Release is intended to enable enterprise customers to clean up their messy data. One key component of the update is improved integration capabilities for data stored in Databricks and Google BigQuery, according to Catanzano.

The Fall 2024 Release includes an integration between Informatica’s no-code tools and Databricks’ generative AI capabilities; an SQL-based data transformation feature that enables users to process extract, load and transform (ELT) pipelines in Databricks Delta Lake and Google BigQuery’ and a task wizard that helps guide users as they ingest and replicate data for AI projects.

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“Aligning with Databricks is a solid step since they are moving quickly with their [generative AI capabilities],” Catanzano said. “As an intelligent data management platform, Informatica needs to be well integrated wherever their customers are or want to be as a management layer.”

Petrie likewise noted the significance of adding ELT pipelines to Delta Lake and BigQuery.

“The ELT enhancements make a lot of sense,” he said. “Many data teams now favor ELT … [SS1] [EA2] because they can perform sophisticated transformations on data after ingesting it into platforms such as Databricks and Snowflake.”

Informatica’s Fall 2024 Release also includes the following:

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  • Turbo-charged Application Integration Runtime, a feature scheduled for general availability in November that aims to improve application performance with autoscaling, high throughput and low latency integration capabilities and includes a serverless option.
  • Prebuilt integration templates for integrating data stored in AWS, Microsoft Azure, Google and Oracle, among others.
  • Connectors to various AI development environments such as Amazon Bedrock and Google Vertex AI as well business and messaging applications including Coupa, Salesforce Streaming Events and Azure Service Bus.
  • New master data management features designed to improve workflow integration.
  • Improved data governance capabilities including metadata access controls in Informatica’s Cloud Data Governance and Data Catalog.
  • Expanded regional availability of Claire GPT.

Petrie noted that Informatica’s update contains a wide range of new and improved features. Perhaps most significant is that they complement one another with a tool such as Turbo-charged Application Integration Runtime targeting the speed and efficiency of integrations enabled by connectors and prebuilt integration templates.

“Informatica’s enhancements for application integration make a lot of sense,” Petrie said. “To differentiate themselves, AI adopters must optimize the user experience with custom applications based on governed, well-integrated data. Informatica is helping companies do this faster and more efficiently on popular data platforms with its new templates and connectors.”

While enabling customers to prepare their data for training AI models and applications is the intent of Informatica’s latest update, the impetus for adding capabilities aimed getting data ready for AI came from a combination of customer feedback and the vendor’s own research, according to Pathak.

“Customer requirements … are always major drivers, along with our own research and development,” he said. “Today, many business and tech leaders are looking to accelerate their GenAI projects and strategic initiatives. We’re helping them with these latest innovations.” 

Next steps

Although Informatica’s Fall 2024 Release focuses on enabling customers to prepare data for training AI models and applications, it does not address the actual development of AI tools other than providing integrations, Catanzano noted.

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Last May, Informatica introduced a low-code/no-code environment for developing AI models and applications. Included are drag-and-drop capabilities, customizable templates, prebuilt techniques for generative AI development and support for a variety of LLMs and vector databases.

The vendor’s latest platform update includes integrations and connectors with development environments from other vendors such as Databricks and Google but does not include new and improved features for its own development environment.

As a result, Catanzano suggested that Informatica focus some of its future product development and marketing on its own tools for model and application developers.

“I think [Informatica should do] more to get customers to see that their platform is where they should be looking to build GenAI solutions,” he said. “They focus on getting your data ready, but I haven’t seen much about where to go next.”

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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.


 [EA2]Sure, good with me.

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SpaceX to top the Super Heavy catch with another astonishing feat

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SpaceX to top the Super Heavy catch with another astonishing feat

SpaceX achieved a spectacular first on Sunday when it used a pair of giant mechanical arms to catch the 70-meter-tall Super Heavy booster just minutes after it deployed the Starship spacecraft to orbit in the vehicle’s fifth test flight.

But SpaceX isn’t stopping there. As part of its efforts to create a fully reusable spaceflight system for the Starship — comprising the first-stage Super Heavy booster and the upper-stage Starship spacecraft — SpaceX will attempt to catch not only the booster, but also the spacecraft.

SpaceX CEO Elon Musk confirmed the plan for the world’s most powerful rocket in a post on X ( formally Twitter) on Wednesday, saying, “Hopefully early next year, we will catch the ship too.”

Before then, SpaceX will want to carry out more test flights of the Starship in which it will continue to catch the Super Heavy, while the Starship will continue to come down in the ocean, as it did in Sunday’s test flight.

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Catching the Starship back at the launch base will allow for a faster turnaround time between launches, with the spacecraft only needing to be checked, refurbished, and refueled before being lifted atop a Super Heavy for another flight.

SpaceX also has to perfect a landing system for the Starship that involves it touching down on the ground in a vertical position, as this is how it will arrive on other celestial bodies such as the moon and possibly Mars (at least until any launch and landing infrastructure can be built).

It’s actually already achieved such a landing in Earth-based tests several years ago, but those touchdowns involved shorter “hops” into the atmosphere rather than more complex orbital flights.

It’s certainly an exciting time for SpaceX engineers as they put much of their attention into the continued development of the Starship.

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NASA is planning to use SpaceX’s spacecraft to put two astronauts on the lunar surface in the Artemis III mission, which is currently scheduled for 2026, so there is much work to be done.






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Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max

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Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max

Both Xiaomi and Apple launched very compelling flagship smartphones this year. In this article, we’ll compare the two. It’s the comparison between the Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max. These two phones are actually quite different in every way. Their internals are far different, and so are their designs. They are both large-format smartphones, though, and do have some things in common.

The Xiaomi 14 Ultra arrived back in February this year, while the iPhone 16 Pro Max followed in December. Both phones are available globally, and both of them are actually quite pricey. Comparing them makes all the sense in the world. We’ll first list their specifications, and will then move to a number of other categories, including design, display, performance, battery, cameras, and audio.

Specs

Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max, respectively

Screen size:
6.73-inch LTPO AMOLED display (curved, adaptive 120Hz, 3,000 nits max brightness)
6.9-inch LTPO Super Retina XDR OLED ( flat, 120Hz, HDR, 2,000 nits)
Display resolution:
3200 x 1440
2868 x 1320
SoC:
Qualcomm Snapdragon 8 Gen 3
Apple A18 Pro (3nm)
RAM:
16GB (LPDDR5X)
12GB/16GB (LPDDR5X)
Storage:
512GB (UFS 4.0)
256GB/512GB/1TB (NVMe)
Rear cameras:
50MP (wide, f/1.6-f/4.0 variable aperture, OIS, multi-directional PDAF, 1.6um pixel size), 50MP (ultrawide, f/1.8 aperture, 122-degree FoV, 0.7um pixel size, dual pixel PDAF), 50MP (telephoto, f/1.8 aperture, 0.7um pixel size, dual pixel PDAF, OIS, 3.2x optical zoom), 50MP (periscope telephoto, f/2.5 aperture, 0.7um pixel size, dual pixel PDAF, OIS, 5x optical zoom)
48MP (wide, f/1.8 aperture, 1/1.28-inch sensor, 1.22um pixel size, sensor-shift OIS), 48MP (ultrawide, f/2.2 aperture, 0.7um pixel size, PDAF), 12MP (periscope telephoto, f/2.8 aperture, 1/3.06-inch sensor, 1.12um pixel size, 3D sensor-shift OIS, 5x optical zoom).
Front cameras:
32MP (wide, f/2.0 aperture, 0.7um pixel size)
12MP (f/1.9 aperture, PDAF, 1/3.6-inch sensor size, OIS)
Battery:
5,000mAh
4,685mAh
Charging:
90W wired, 80W wireless,, 10W reverse wireless (charger included)
38W wired, 25W MagSafe, 15W Qi2 wireless, 7.5W Qi wireless, 4.5W reverse wired (charger not included)
Dimensions:
161.4 x 75.3 x 9.2mm
163 x 77.6 x 8.3 mm
Weight:
219.8 grams
227 grams
Connectivity:
5G, LTE, NFC, Wi-Fi, USB Type-C, Bluetooth 5.4/5.3
Security:
In-display fingerprint scanner & facial scanning
Face ID (3D facial scanning)
OS:
Android 14 with HyperOS
iOS 18
Price:
€1,499
$1,199+
Buy:
Xiaomi 14 Ultra (Amazon)
Apple iPhone 16 Pro Max (Apple)

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Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max: Design

The Xiaomi 14 Ultra is made out of aluminum and glass. The thing is, there is a vegan leather model out there too, but only in China. There is also a variant with a titanium frame, but only in China. The iPhone 16 Pro Max, on the other hand, is made out of titanium and glass. There is only one variant in terms of build materials. The iPhone 16 Pro Max is slightly taller, wider, and thinner than the Xiaomi 14 Ultra. It’s heavier than the global variant of the Xiaomi 14 Ultra, but lighter than one of the models of Xiaomi’s flagship, it all depends. Both phones are set between 220 and 230 grams, though, so they’re not particularly light.

You’ll find flat sides on both of these phones, though the implementation is a bit different. The Xiaomi 14 Ultra’s back side is not completely flat, unlike what the iPhone 16 Pro Max offers. A flat display is included on both phones, though, along with thin bezels. The Xiaomi 14 Ultra has a display camera hole at the top of its display, while the iPhone 16 Pro Max includes a pill-shaped cutout known as Dynamic Island.

The Xiaomi 14 Ultra has its power/lock and volume rocker buttons on the right-hand side. Those are the only buttons included on the phone. The iPhone 16 Pro Max has two more. It includes its power/lock button on the right side, along with the Camera Control key. On the left, you’ll find the volume up and down buttons, and the Action Button. The Xiaomi 14 Ultra also has an IR blaster at the top.

You’ll notice a big camera oreo on the back of the Xiaomi 14 Ultra. Four cameras sit in there, and that camera island does protrude quite a bit on the back. The iPhone 16 Pro Max has a much smaller camera island in the top-left corner of its back. Three cameras sit on the inside. Both smartphones are IP68 certified for water and dust resistance. They’re both quite slippery too, though the vegan leather model of the Xiaomi 14 Ultra does add more grip.

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Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max: Display

The Xiaomi 14 Ultra features a 6.73-inch 3200 x 1440 LTPO AMOLED display. That panel is flat, and it supports an adaptive refresh rate of up to 120Hz. It also supports Dolby Vision and HDR10+ content. The peak brightness here is 3,000 nits, in theory, and the screen-to-body ratio is at around 89%. The display aspect ratio is 20:9, while the Xiaomi Shield Glass protects this display.

Apple iPhone 16 Pro AM AH 24

The iPhone 16 Pro Max, on the other hand, has a 6.9-inch 2868 x 1320 LTPO Super Retina XDR OLED display. This display is also flat, and it offers an adaptive refresh rate of up to 120Hz. HDR10 content is supported, as is HDR10 content, while the peak brightness is at 2,000 nits. The screen-to-body ratio sits at around 91%, while the display aspect ratio is 19.5:9. The Ceramic Shield glass protects this display.

Both of these displays are great. They’re both sharp, vivid, and have great viewing angles. They also get more than bright enough and have those inky blacks that people love. The Xiaomi 14 Ultra’s panel does get a bit brighter when needed. It also supports high-frequency PWM dimming, unlike the iPhone 16 Pro Max’s panel. Both displays do offer really good touch response, though. You’ll likely be more than happy with either one of these two panels.

Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max: Performance

The Xiaomi 14 Ultra is fueled by the Snapdragon 8 Gen 3 processor, a 4nm chip. That is still Qualcomm’s best chip, even though its successor is coming later this month. That chip is backed with up to 16GB of LPDDR5X RAM and UFS 4.0 flash storage. The iPhone 16 Pro Max is fueled by the Apple A18 Pro processor, which is a 3nm chip. That processor is backed by 8GB of RAM and NVMe flash storage. Neither phone supports storage expansion, by the way.

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Both of these processors are immensely powerful, as are both phones in general. In day-to-day use, no matter what you use them for, both smartphones deliver outstanding performance. They’re very snappy in every way, handling browsing, image editing, multimedia consumption, and everything else is not a problem. Getting both phones to stutter is not an easy task, actually.

The same can be said for gaming. They can play simpler games without a problem, and the same goes for semi-demanding and truly graphically-demanding games. Both of these phones can handle even the most demanding games on their respective app stores without a problem. They both get warm, but not too warm nor does that affect their gaming performance. Genshin Impact, for example, is not a problem for either phone.

Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max: Battery

A 5,000mAh battery sits inside the global Xiaomi 14 Ultra model. The Chinese variant does include a 5,300mAh unit, but that’s not the one we used. The iPhone 16 Pro Max features a 4,685mAh battery. Apple’s iPhones always have smaller battery packs than their Android counterparts, mainly due to the differences in how iOS and Android function. That doesn’t have to mean that the iPhone 16 Pro Max has worse battery life. And in this case, it does not.

The Xiaomi 14 Ultra has great battery life in its own right, but the iPhone 16 Pro Max shades it in that regard. Both smartphones can go up to 7 hours of screen-on-time, and then some. The iPhone 16 Pro Max always has more battery juice left at that point, quite a bit more. We were able to push it way past that point. In all honesty, the Xiaomi 14 Ultra can also go higher than that, but it cannot keep up with the iPhone 16 Pro Max.

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Do note that we gaming does affect battery life quite a bit, as do other demanding tasks. Even when we did play games during the day, both of these phones were able to go the distance. Their battery life is so good that even demanding users will be pleased, though your mileage may vary, of course.

When it comes to charging, the Xiaomi 14 Ultra shames the iPhone 16 Pro Max. It supports 90W wired, 80W wireless, and 10W reverse wireless charging. The iPhone 16 Pro Max supports 38W wired, 25W MagSafe wireless, 15W Qi2 wireless, 7.5W Qi wireless, and 4.5W reverse wired charging. The thing is, the Xiaomi 14 Ultra also comes with a charger, unlike the iPhone 16 Pro Max.

Xiaomi 14 Ultra vs Apple iPhone 16 Pro Max: Cameras

The Xiaomi 14 Ultra has four 50-megapixel cameras on the back. Its main 50-megapixel camera includes a 1-inch type sensor and variable aperture. A 50-megapixel ultrawide camera (122-degree FoV) is also included, as is a 50-megapixel telephoto camera (3.2x optical zoom). The last camera on the back is a 50-megapixel periscope telephoto unit (5x optical zoom). All those cameras use Leica lenses.

Xiaomi 14 Ultra AM AH 16

The iPhone 16 Pro Max, on the flip side, has a 48-megapixel main camera (1/1.28-inch sensor), a 48-megapixel ultrawide unit, and a 12-megapixel periscope telephoto camera (5x optical zoom). The thing is, all three cameras on the back of the iPhone 16 Pro Max have smaller sensors than their counterparts on the Xiaomi 14 Ultra. On top of that, the iPhone 16 Pro Max does not offer variable aperture.

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Both smartphones are very capable in the camera department, though. They do offer considerably different results. The Xiaomi 14 Ultra shoots more contrasty shots that are closer to real life. The iPhone 16 Pro Max does love to use warmer color tones in images, and the images do look more processed in comparison. It’s all a matter of preference. We personally preferred shots from the Xiaomi 14 Ultra most of the time, and that is especially true for low light.

The Xiaomi 14 Ultra does do a better job with telephoto shots, especially those up to 5x. Their ultrawide cameras are about on par when it comes to performance. Both smartphones are very capable when it comes to macro photography, though we did prefer such photos from the iPhone 16 Pro Max. Apple’s flagship still has the upper hand in the video department.

Audio

Both of these smartphones include stereo speakers. Those speakers on both are more than loud enough, though the ones on the iPhone 16 Pro Max seem to be a bit louder. That’s not something everyone will notice, though. The sound quality is good from both phones.

Neither smartphone includes an audio jack, however. You can still use their Type-C ports for wired audio connections, though. Alternatively, the Xiaomi 14 Ultra offers Bluetooth 5.4, while the iPhone 16 Pro Max supports Bluetooth 5.3.

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Apple will launch a Business Caller ID service next year

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Apple will launch a Business Caller ID service next year

Apple some new tools to its Apple Business Connect program that could be useful for the everyday consumer. The most notable update is the introduction of Business Caller ID. When this feature rolls out next year, companies of any size can register to have their name, logo and department appear when they contact customers. In practice, that can help people distinguish between a phone call from a legitimate business and spam.

Apple Business Connect allows companies to have more control over how they appear within different apps across the Apple ecosystem. In 2023, Apple businesses customization for their listings in Maps, Messages, Siri and Wallet. Today’s updates make Business Connect branding tools available to any company, including those without a brick-and-mortar location. In addition to the eventual rollout of Business Caller ID, the program is also adding brand info within the Mail and Phone apps. Participating companies can also add their logo to the feature for contactless payments.

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Games VC funding is stabilizing, but growth-stage funding is up | Konvoy

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Games VC funding is stabilizing, but growth-stage funding is up | Konvoy

Gaming VC fund Konvoy Ventures released its latest report on the state of funding in the industry. According to its findings, venture capital funding is overall up about 1% quarter-over-quarter, but growth-stage funding has increased. The overall number of deals has also gone down QoQ.

Konvoy’s findings show that the games industry is expected to be $188 billion market in 2024, and a $223 billion market by 2029. Private funding for games in Q3 2024 totals $811 million, a 15% increase from the previous quarter. The total amount of private funding for three-quarters of the year so far is higher than 2023’s overall total for four quarters — however, this is mostly due to Disney’s $1.5 billion investment in Epic Games.

The total number of VC deals in gaming was 92 for this quarter, a 14% QoQ decrease. Growth-stage funding — funding for Series B-D — was $262 million, higher than 2023’s average of $159 million. Early-stage funding, on the other hand — pre-seed through Series A — is the lowest its been since Q1 2020.

Jason Chapman, Konvoy’s managing partner, told GamesBeat in an interview, “We’re seeing encouraging signs of normalization in gaming VC funding over the past six quarters, despite macroeconomic challenges. The gaming industry continues to command and demand people’s time, proving its resilience. However, while the volume of AI-related gaming deals have grown, traditional content studios are facing compression in VC funding. Content alone doesn’t seem to be a strong fit for venture capital at this stage.”

Konvoy’s report: AI-based funding

One of the insights from Konvoy’s report is the increase of investment in gaming companies related to or referencing AI. 22% of funding for Q3 went to such companies, or $113 million. That’s up from 10% and $52 million in the previous quarter. According to the report, two of the largest investments in AI companies happened in Q3: Volley’s $55 million fundraise and Series Entertainment’s $28 million Series A funding round.

Chapman told GamesBeat, “We’re seeing strong VC interest in AI-powered gaming startups, particularly those focused on virtual characters that enhance the player experiences. There’s significant funding traction in startups that help game studios produce and edit content faster, especially in areas like art and video creation, which represent a large portion of production costs. These AI-driven tools are streamlining game development and attracting more attention from investors.”

Konvoy’s complete Gaming Industry Report includes regional insights and is now available on the company’s website.

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ODD taps $27M for diamond chips to clear radioactive debris at Fukushima Daiichi Nuclear Power Plant

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ODD taps $27M for diamond chips to clear radioactive debris at Fukushima Daiichi Nuclear Power Plant

Back in 2011, the world held its breath after the Fukushima Daiichi nuclear plant in Japan suffered a failure of its cooling systems, in the wake of the country getting hit by a 9.0 magnitude earthquake and tsunami. The worry was not unfounded: the resulting meltdown — which spread highly radioactive material in multiple directions — became one of the worst nuclear-related disasters of all time.

More than a decade on, the clean-up is still in progress. Last month, the Japanese government began a testing procedure to remove radioactive debris in and around the plant — a significant step in the plant’s decommissioning process, expected to be completed by 2051.

A groundbreaking startup from Japan, Ookuma Diamond Device (ODD), is playing a fascinating part in the process, by way of diamond chips that are being used in efforts to remove radioactive debris, by way of diamond-chip-powered amplifiers. And now, it has raised 4 billion yen, equivalent to approximately $27 million, to build the world’s first diamond semiconductor manufacturing facility in nearby Ookuma, also in Fukushima.

ODD’s plans are to build the factory in January 2025 and have it up and running by Summer 2026.

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Why use diamond chips rather than traditional silicon-based semiconductors?

Diamond is known as a wide-bandgap (WBG) semiconductor material — others include SiC (silicon carbide) and GaN (gallium nitride). WBG materials are considered to have better power conversion efficiency and exceptional thermal management.

Unlike silicon-based CPUs, GPUs, and NPUs, but the diamond-based chip do not have a circuit structure. Diamond semiconductors act more like powerful control devices than small electricity sources, Cocal Capital partner Ken Nishimura told TechCrunch. He said that the diamond semiconductor will be used in larger facilities such as nuclear power plants that require super high temperatures and radiation levels, which silicon-based chips cannot withstand.

Diamond semiconductor amplifiers operating under 300°C have been successfully prototyped using the National Institute of Advanced Industrial Science and Technology (AIST) and Hokkaido University facilities.

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“Diamond semiconductors, which we develop, are fundamentally different from traditional silicon-based chips due to their superior material properties,” Yuhei Nagai, CFO of Ookuma Diamond Device, said in an exclusive interview with TechCrunch. Compared to other advanced semiconductors like SiC and GaN, diamond semiconductors provide superior power conversion efficiency and improved thermal management for next-generation technologies such as 6G, space, defense, and nuclear, he continued.

It’s also notable that diamond chips can be made from methane gas, potentially enabling full production in Japan. This is in contrast to GaN, which relies sourcing materials heavily controlled by China.

ODD’s focus is on developing “pure diamond semiconductors,” rather than GaN semiconductors on a diamond substrate, Nagai said. The market size for diamond materials used in chips is expected to grow to $10 billion by 2032, up from $113.7 million in 2023., according to a recent report.

Image Credits:Ookuma Diamond Device (ODD)

The startup, a spinout from Japan’s National Institute of Advanced Industrial Science and Technology (AIST) and Hokkaido University, was specifically founded in 2021 to help with decommissioning the Fukushima Daiichi Nuclear Power Plant.

Two co-founders, Dr. Junichi Kaneko and Dr. Hitoshi Umezawa, have researched diamond chips for over 20 years. They found their work thrown into the spotlight after the disaster, which spelled more resources for R&D and spurred the founding of the startup. ODD built the world’s first practical diamond chip in 2021.

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The leaps between theory, chip, and final product are still significant. The two co-founders are also leading the Japanese government’s wider national project to make an actual product that could remove radioactive debris from natural disasters. 

“The [ODD’s] prototypes represent a world-first achievement—no one else has been able to develop functioning diamond semiconductor amplifiers to this point,” said Nagai.

A handful of global companies are also developing diamond semiconductors, including Diamfab in France, Element Six in the U.K., and A.L.M.T. in Japan, a subsidiary of Sumitomo Electric Industries.

ODD sets itself apart by claiming to be the only one with end-to-end expertise, from substrate to packaging, enabling the world’s prototype of a diamond semiconductor amplifier.

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ODD is also talking with more than 10 potential customers worldwide in the nuclear power plant, aerospace, and telco industries, Nagai said — an area that this week got increased focus after it emerged that Google signed a deal to work on powering data centers with nuclear power.

Globis Capital partners led the recent funding, which brings its total raised to approximately $45 million (6.7 billion yen) since its inception, with participation from Coral Capital, aSTART, Green Co-Invest Investment, Japan Post Bank Spiral Regional Innovation Fund, Mitsui Sumitomo Insurance venture capital, SMBC Venture Capital, among others.

The startup, which currently has 27 employees, has also received around $15 million in government grants from the Cabinet Office, METI, MIC, ATLA, and the Reconstruction Agency.

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Meta is laying off employees at WhatsApp, Instagram, and more

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Meta is laying off employees at WhatsApp, Instagram, and more

Meta has begun laying off employees across various departments, including WhatsApp, Instagram, and Reality Labs, according to people familiar with the matter. Rather than a mass, companywide layoff, these smaller cuts seem to coincide with reorganizations of specific teams.

Some Meta employees have started posting that they’ve been laid off. Among them is Jane Manchun Wong, who gained notoriety for reporting on unannounced features coming to apps before joining the Threads team in 2023.

The Verge asked Meta to confirm the layoffs and will update this story if we receive a statement.

This new round of layoffs follows a small series of job cuts in the company’s Reality Labs division earlier this year. Meta first laid off 11,000 employees in 2022 following overoptimism about the company’s growth coming out of the covid pandemic. It then announced cuts of 10,000 more people as part of CEO Mark Zuckerberg’s “year of efficiency” in 2023.

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