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You can now fine-tune your own version of AI image maker Flux with just 5 images

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Black Forest Labs has quickly made a name for itself as the premiere, high-quality open-source AI image generation startup — even surpassing the quality of models offered by Stability AI, where Black Forest Labs’ founders previously worked. […]

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Black Forest Labs has quickly made a name for itself as the premiere, high-quality open-source AI image generation startup — even surpassing the quality of models offered by Stability AI, where Black Forest Labs’ founders previously worked. It briefly served as the default image generator in xAI’s Grok language model, too.

Credit: Artificial Analysis

Today Black Forest Labs is taking this a step further, announcing the release of the FLUX Pro Finetuning API, a tool that empowers creators to customize generative AI models using their own images and concepts.

Designed for professionals in marketing, branding, storytelling and other creative industries, the API enables the personalization of the company’s flagship FLUX Pro and FLUX Ultra models with a user-friendly approach.

Customization at scale

The FLUX Pro Finetuning API allows users to fine-tune generative text-to-image models with five to 20 training images, optionally accompanied by text descriptions.

This process results in customized models that maintain the generative versatility of the base FLUX Pro models while aligning outputs with specific creative visions. The tool supports multiple modes, including “character,” “product,” “style” and “general,” making it adaptable for a wide variety of use cases.

The trained models can seamlessly integrate with endpoints such as FLUX.1 Fill, Depth, Canny and Redux, as well as with high-resolution generation capabilities of up to four megapixels. Whether for creating brand-consistent marketing visuals or detailed character art, the API enhances precision and adaptability in AI-generated content.

Practical applications and use cases for brands, marketers and more

Using the FLUX Pro Finetuning API, professionals can create customized models that preserve essential design elements, character consistency or brand properties. A study conducted by Black Forest Labs showed that 68.9% of users preferred FLUX Pro’s fine-tuned results over competing services.

Some highlighted applications include:

Inpainting: Using FLUX.1 Fill for iterative edits to refine images

Structural Control: Integrating with FLUX.1 Depth to enhance image generation with precise structural adjustments

Visual Branding: Ensuring consistency across marketing materials and campaigns

Partnership with BurdaVerlag

Black Forest Labs has partnered with BurdaVerlag, a leading German media and entertainment company, to demonstrate the potential of the FLUX Pro Finetuning API. BurdaVerlag’s creative teams are using the tool to develop customized FLUX models tailored to their brands, such as the children’s publication Lissy PONY.

With this integration, BurdaVerlag’s design teams can create visuals that reflect each brand’s identity while exploring new creative directions. The API has accelerated their production workflows, enabling high-quality content generation at scale.

Accessible pricing and availability

The FLUX Pro Finetuning API is now available via API endpoints through the Flux.1 [dev] model. Pricing for all FLUX models on Black Forest Labs’ API is as follows:

FLUX 1.1 [pro] Ultra: $0.06 per image

FLUX 1.1 [pro]: $0.04 per image

FLUX.1 [pro]: $0.05 per image

FLUX.1 [dev]: $0.025 per image

Getting started is a cinch

The finetuning process requires minimal input from users. Training images in supported formats (JPG, JPEG, PNG or WebP) are uploaded, with resolutions capped at one megapixel for optimal results. Advanced configuration options allow for fine control over the training process, including iteration counts, learning rates, and trigger words for precise prompt integration.

Black Forest Labs has also provided extensive resources, including a Finetuning Beta Guide and Python scripts for easy implementation. Users can monitor progress, adjust parameters, and test results directly via API endpoints, ensuring a smooth and efficient workflow.

By combining versatility, ease of use and professional-grade outputs, the FLUX Pro Finetuning API sets a new benchmark for customized content creation in generative AI. With the tool now available, Black Forest Labs aims to transform how individuals and organizations approach personalized media generation, unlocking creative possibilities at an unprecedented scale.

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Governing AI in utilities: Insights from West Monroe’s AI summit

The rapid evolution of artificial intelligence (AI) presents both opportunities and risks for the utility sector. Infrastructure owners are no strangers to navigating emerging challenges—whether it’s environmental standards, field device modernization, or cybersecurity. But AI represents a new frontier, where the pace of technological change and regulatory complexity demands a

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Kyndryl service aims to control agentic AI across the enterprise

Kyndryl has launched a new service aimed at helping customers manage the growing use of AI agents across the enterprise. Its Agentic AI Framework is an orchestration platform built to deploy and manage autonomous, self-learning agents across business workflows in on-prem, cloud, or hybrid IT environments, according to the company. 

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Why enterprises need to drive telecom standards

Cutting access costs by supporting VPN-over-FWA or standardizing SD-WAN interconnects could save enterprises as much as a quarter of their VPN costs, but neither is provided in 5G or assured in 6G. Enterprises could change that if they applied appropriate pressure. Reason No. 3: Satellite, private mobile, public mobile, and

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Petronas Brings SMJ Energy Onboard Its Third FLNG Project

Malaysia’s Petroliam Nasional Bhd. (Petronas), through its subsidiary Petronas LNG Sdn. Bhd. (PLSB), has signed a heads of agreement (HoA) with SMJ Energy Sdn. Bhd. that formalizes the terms for SMJ Energy’s 25 percent equity participation in PFLNG 3 Sdn. Bhd. Petronas said in a media release the new agreement is a “significant step forward” in its efforts to strengthen its partnership with Sabah’s state government. Dionysia Aloysius Kibat, SMJ Energy CEO, and Shamsairi M Ibrahim, PLSB CEO, signed the agreement. PFLNG 3 is the project company tasked with the upcoming shore-based floating liquefied natural gas (LNG) facility in the Sipitang Oil and Gas Industrial Park (SOGIP) in Sabah. The PFLNG 3 is Petronas’ third FLNG facility. According to the company, it is the first nearshore FLNG facility in the world. The facility will produce up to 2 million tonnes of LNG per annum and is scheduled to start production in 2027. The engineering, procurement and construction contracts have gone to JGC Holdings Corp. and Samsung Heavy Industries. The proposed equity acquisition will be implemented via definitive agreements to be finalized following the HoA, Petronas said. Earlier this month, Petronas formalized several key agreements with the state of Sabah through its unit, Malaysia Petroleum Management. These deals are part of the Commercial Collaboration Agreement that Petronas signed with the state government in 2021. The collaboration agreement aims for a long-term and structured approach to securing a reliable gas supply for the state’s expanding domestic demand, while enabling sustainable industrial growth, according to Petronas. Both Petronas and SMJ Energy are part of the task force that developed the Sabah Gas Strategy. To contact the author, email [email protected] What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The Rigzone Energy Network is a

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Technip, Shell Tie Up for Carbon Capture Projects

Technip Energies NV has partnered with Shell Catalysts & Technologies Ltd. to exclusively work together on a post-combustion amine-based carbon capture solution. The two companies, according to a joint statement, will use Shell’s CANSOLV carbon dioxide capture system. The alliance leverages Shell Catalysts & Technologies’ technology expertise with Technip Energies’ strength in integration and project delivery, the companies said. The parties have committed to working exclusively together to offer an improved, complementary solution in the post-combustion carbon capture sector. Shell Catalysts & Technologies and Technip Energies believe this model will make carbon capture more attractive, scalable, and accessible for industrial sectors, aiding customers in decarbonization efforts. “This agreement marks a significant milestone in a relationship built on shared ambition and delivery. Through our strengthened alliance with Technip Energies, we’re helping customers advance their decarbonization plans, backed by deep expertise and more than a decade of working side by side”, Robin Mooldijk, President for Projects and Technology at Shell, said. “By forming a global alliance with Shell Catalysts & Technologies in the field of carbon capture, we combine cutting-edge technology, smart engineering, and excellence in project execution. This global alliance is the result of more than 10 years of collaboration and continuous innovation,” Arnaud Pieton, Chief Executive Officer of Technip Energies, added. “Our ambition is to deliver a world designed to last by enabling hard-to-abate industries to decarbonize with greater certainty and affordability. “Canopy by T.EN, powered by Shell CANSOLV carbon capture solution, pragmatically delivers on this ambition”. To contact the author, email [email protected] What do you think? We’d love to hear from you, join the conversation on the Rigzone Energy Network. The Rigzone Energy Network is a new social experience created for you and all energy professionals to Speak Up about our industry, share knowledge, connect with peers and industry insiders and engage in

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CEP Makes ‘Major’ Oil Discovery offshore Poland

Central European Petroleum (CEP) announced Monday a “major” oil discovery in the Wolin concession on Poland’s side of the Baltic Sea. The Canadian explorer and producer estimates that the Wolin East 1 discovery well holds mean recoverable oil, sales gas and natural gas liquids of 200 million barrels of oil equivalent (MMboe). Based on the estimate, “the oil and gas resources in Wolin East constitute the largest conventional hydrocarbon field yet discovered in Poland, and one of the largest conventional oil discoveries in Europe in the past decade”, CEP said in a statement online. The well was drilled by a jack-up rig in waters 9.5 meters (31.17 feet) deep and about six kilometers (3.73 miles) from the city of Swinoujscie. Drilling reached a vertical depth of 2,715 meters. “Tests confirmed a 62-meter hydrocarbon column and excellent reservoir properties for oil and gas production in the Main Dolomite geological formation”, CEP said. “There is also significant further low-risk exploration, appraisal and secondary recovery potential within the license in the Main Dolomite as well as in the deeper Rotliegend formation”, it added. “With these opportunities included, the Wolin license in total is estimated to contain more than 400 MMboe of recoverable hydrocarbon resources”, CEP said. Krzysztof Galos, undersecretary of state and chief national geologist, said, “The discovery of the Wolin East hydrocarbon deposit – although it still requires the preparation, submission, and approval of the deposit’s geological documentation – may prove to be one of the breakthrough moments in the history of hydrocarbon exploration in Poland, especially with regard to areas that have so far remained insufficiently explored, such as Poland’s Exclusive Economic Zone in the Baltic Sea”. “If this discovery is ultimately confirmed, the Wolin East deposit could become the largest oil and associated natural gas field discovered in Poland to date”, Galos

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Oil Slides Amid Demand Concerns

Oil edged down, extending its losing streak from last week, on lingering worries about crude demand as US trade talks stall and the European Union’s latest sanctions have yet to dent Russian energy exports. West Texas Intermediate crude ended the day marginally lower near $67 a barrel on Monday, after slipping 1.6% last week. EU envoys are set to meet as early as this week to formulate a plan to respond to a possible no-deal scenario with US President Donald Trump, whose position is seen to have stiffened ahead of an Aug. 1 deadline. Late last week, the 27-nation bloc agreed on a package of sanctions against Moscow, including a lower price cap on the country’s crude and a ban on a large refinery in India. Still, restrictions on Russian diesel won’t fully come into effect until January. US crude futures for August delivery are set to expire on Tuesday, contributing to muted volumes and listless trading. Oil has trended higher since early May, but WTI is still down for the year as Trump ratchets up his trade war and OPEC+ relaxes supply curbs. Prices have been jolted by developments in the Middle East, as well as sanctions on crude from producers including Russia and Iran. “In the absence of catalysts, the path of least resistance could be lower,” said Rebecca Babin, a senior energy trader at CIBC Private Wealth Group. Diesel’s price relative to crude in Europe, a gauge for profitability of producing the fuel, was near the highest since early 2024, while its prompt time spread — the difference between its closest two contracts — also rallied on Friday, widening its bullish backwardation structure. Oil Prices WTI for August delivery, which expires Tuesday, edged 14 cents lower to settle at $67.20 a barrel in New York. The more

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Treasury Sec Says China Talks Could Include Its Russia, Iran Oil Purchases

Treasury Secretary Scott Bessent said the next round of US-China talks could include a discussion of China’s purchases of Russian and Iranian oil, a signal that the focus could shift from more traditional trade issues to ones that cross over into matters of national security. “Trade is in a good place,” Bessent said on CNBC, referring to recent and ongoing negotiations with China. “And I think now we can start talking about other things. The Chinese, unfortunately, are very large purchasers of sanctioned Iranian oil, sanctioned Russian oil — so we could start discussing that.” Bessent was also asked about new sanctions on Russia, and he hinted the US was more likely to pursue a tariff-based strategy that would impose hefty duties on any country it found to be purchasing sanctioned Russian energy. “Any country who buys sanctioned Russian oil is going to be subject to up to 100% secondary tariffs,” he said. “President Trump has changed the conversation here and I would urge our European allies, who have talked a big game, to follow us if we implement these secondary tariffs.” President Donald Trump last week threatened “very severe tariffs if we don’t have a deal in 50 days” on the Russia-Ukraine war. “tariffs at about 100%.” WHAT DO YOU THINK? Generated by readers, the comments included herein do not reflect the views and opinions of Rigzone. All comments are subject to editorial review. Off-topic, inappropriate or insulting comments will be removed.

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UK Joins EU in Lowering Price Cap on Russian Oil

The UK joined the European Union’s efforts to diminish Russia’s revenues further by lowering the price cap on its crude oil, extending a broader push to pressure the Kremlin for continuing the war in Ukraine.  The cap on Russian oil, currently set at $60 per barrel, will be lowered to $47.60 on September 2, the UK government announced Friday. The price caps of $100 on high-value refined oil products, such as diesel and petrol, and $45 on low-value refined oil products, such as fuel oil, remain unaffected. EU states earlier approved a fresh sanctions package on Russia that included new banking restrictions and curbs on fuels made from the nation’s petroleum. The package – the bloc’s 18th since Moscow’s full-scale invasion of Ukraine – will also cut off 20 more Russian banks from the international payments system SWIFT and impose restrictions on Russian petroleum refined in other countries. A large oil refinery in India, part-owned by Russia’s state-run oil company, Rosneft PJSC, was also blacklisted. The latest sanctions from the UK and EU are aimed at further crimping the Russia’s energy revenue, the bulk of which comes from oil exports to India and China. It comes after the original price cap imposed by the Group of Seven had a limited impact due to a large shadow fleet of tankers that haul its oil without using western services. The revised cap approved by the EU will be set at 15 percent below market rates moving forward and revised automatically at least twice a year. “This decisive step to lower the crude Oil Price Cap will target Russia’s oil revenues and ramp up the pressure on Putin by exploiting his biggest vulnerability – while keeping energy markets stable,” said UK Chancellor of the Exchequer Rachel Reeves.  The UK and EU have so far failed to convince

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‘Significant’ outage at Alaska Airlines not a security incident, but a hardware breakdown

The airline told Network World that when the critical piece of what it described as “third-party multi-redundant hardware” failed unexpectedly, “it impacted several of our key systems that enable us to run various operations.” The company is currently working with its vendor to replace the faulty equipment at the data center. The airline has cancelled more than 150 flights since Sunday evening, including 64 on Monday. The company said additional flight disruptions are likely as it repositions aircraft and crews throughout its network. Alaska Airlines emphasized that the safety of its flights was never compromised, and that “the IT outage is not related to any other current events, and it’s not connected to the recent cybersecurity incident at Hawaiian Airlines.” The airline did not provide additional information to Network World about the specifics of the outage. “There are many redundant components that can fail,” said Roberts, noting that it could have been something as simple as a RAID array (which combines multiple physical data storage components into one or more logical units). Or, on the network side, it could have been the failure of a pair of load balancers. “It’s interesting that redundancy didn’t save them,” said Roberts. “Perhaps multiple pieces of hardware were impacted by the same issue, like a firmware update. Or, maybe they’re just really unlucky.”

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Cisco upgrades 400G optical receiver to boost AI infrastructure throughput

“In the data center, what’s really changed in the last year or so is that with AI buildouts, there’s much, much more optics that are part of 400G and 800G. It’s not so much using 10G and 25G optics, which we still sell a ton of, for campus applications. But for AI infrastructure, the 400G and 800G optics are really the dominant optics for that application,” Gartner said. Most of the AI infrastructure builds have been for training models, especially in hyperscaler environments, Gartner said. “I expect, towards the tail end of this year, we’ll start to see more enterprises deploying AI infrastructure for inference. And once they do that, because it has an Nvidia GPU attached to it, it’s going to be a 400G or 800G optic.” Core enterprise applications – such as real-time trading, high-frequency transactions, multi-cloud communications, cybersecurity analytics, network forensics, and industrial IoT – can also utilize the higher network throughput, Gartner said. 

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Supermicro bets big on 4-socket X14 servers to regain enterprise trust

In April, Dell announced its PowerEdge R470, R570, R670, and R770 servers with Intel Xeon 6 Processors with P-cores, but with single and double-socket servers. Similarly, Lenovo’s ThinkSystem V4 servers are also based on the Intel Xeon 6 processor but are limited to dual socket configurations. The launch of 4-socket servers by Supermicro reflects a growing enterprise need for localized compute that can support memory-bound AI and reduce the complexity of distributed architectures. “The modern 4-socket servers solve multiple pain points that have intensified with GenAI and memory-intensive analytics. Enterprises are increasingly challenged by latency, interconnect complexity, and power budgets in distributed environments. High-capacity, scale-up servers provide an architecture that is more aligned with low-latency, large-model processing, especially where data residency or compliance constraints limit cloud elasticity,” said Sanchit Vir Gogia, chief analyst and CEO at Greyhound Research. “Launching a 4-socket Xeon 6 platform and packaging it within their modular ‘building block’ strategy shows Supermicro is focusing on staying ahead in enterprise and AI data center compute,” said Devroop Dhar, co-founder and MD at Primus Partner. A critical launch after major setbacks Experts peg this to be Supermicro’s most significant product launch since it became mired in governance and regulatory controversies. In 2024, the company lost Ernst & Young, its second auditor in two years, following allegations by Hindenburg Research involving accounting irregularities and the alleged export of sensitive chips to sanctioned entities. Compounding its troubles, Elon Musk’s AI startup xAI redirected its AI server orders to Dell, a move that reportedly cost Supermicro billions in potential revenue and damaged its standing in the hyperscaler ecosystem. Earlier this year, HPE signed a $1 billion contract to provide AI servers for X, a deal Supermicro was also bidding for. “The X14 launch marks a strategic reinforcement for Supermicro, showcasing its commitment

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Moving AI workloads off the cloud? A hefty data center retrofit awaits

“If you have a very specific use case, and you want to fold AI into some of your processes, and you need a GPU or two and a server to do that, then, that’s perfectly acceptable,” he says. “What we’re seeing, kind of universally, is that most of the enterprises want to migrate to these autonomous agents and agentic AI, where you do need a lot of compute capacity.” Racks of brand-new GPUs, even without new power and cooling infrastructure, can be costly, and Schneider Electric often advises cost-conscious clients to look at previous-generation GPUs to save money. GPU and other AI-related technology is advancing so rapidly, however, that it’s hard to know when to put down stakes. “We’re kind of in a situation where five years ago, we were talking about a data center lasting 30 years and going through three refreshes, maybe four,” Carlini says. “Now, because it is changing so much and requiring more and more power and cooling you can’t overbuild and then grow into it like you used to.”

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My take on the Gartner Magic Quadrant for LAN infrastructure? Highly inaccurate

Fortinet being in the leader quadrant may surprise some given they are best known as a security vendor, but the company has quietly built a broad and deep networking portfolio. I have no issue with them being considered a leader and believe for security conscious companies, Fortinet is a great option. Challenger Cisco is the only company listed as a challenger, and its movement out of the leader quadrant highlights just how inaccurate this document is. There is no vendor that sells more networking equipment in more places than Cisco, and it has led enterprise networking for decades. Several years ago, when it was a leader, I could argue the division of engineering between Meraki and Catalyst could have pushed them out, but it didn’t. So why now? At its June Cisco Live event, the company launched a salvo of innovation including AI Canvas, Cisco AI Assistant, and much more. It’s also continually improved the interoperability between Meraki and Catalyst and announced several new products. AI Canvas is a completely new take, was well received by customers at Cisco Live, and reinvents the concept of AIOps. As I stated above, because of the December cutoff time for information gathering, none of this was included, but that makes Cisco’s representation false. Also, I find this MQ very vague in its “Cautions” segment. As an example, it states: “Cisco’s product strategy isn’t well-aligned with key enterprise needs.” Some details here would be helpful. In my conversations with Cisco, which includes with Chief Product Officer and President Jeetu Patel, the company has reiterated that its strategy is to help customers be AI-ready with products that are easier to deploy and manage, more automated, and with a lower cost to run. That seems well-aligned with customer needs. If Gartner is hearing customers want networks

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Equinix, AWS embrace liquid cooling to power AI implementations

With AWS, it deployed In-Row Heat Exchangers (IRHX), a custom-built liquid cooling system designed specifically for servers using Nvidia’s Blackwell GPUs, it’s most powerful but also its hottest running processors used for AI training and inference. The IRHX unit has three components: a water‑distribution cabinet, an integrated pumping unit, and in‑row fan‑coil modules. It uses direct to chip liquid cooling just like the equinox servers, where cold‑plates attached to the chip draw heat from the chips and is cooled by the liquid. The warmed coolant then flows through the coils of heat exchangers, where high‑speed fans Blow on the pipes to cool them, like a car radiator. This type of cooling is nothing new, and there are a few direct to chip liquid cooling solutions on the market from Vertiv, CoolIT, Motivair, and Delta Electronics all sell liquid cooling options. But AWS separates the pumping unit from the fan-coil modules, letting a single pumping system to support large number of fan units. These modular fans can be added or removed as cooling requirements evolve, giving AWS the flexibility to adjust the system per row and site. This led to some concern that Amazon would disrupt the market for liquid cooling, but as a Dell’Oro Group analyst put it, Amazon develops custom technologies for itself and does not go into competition or business with other data center infrastructure companies.

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Microsoft will invest $80B in AI data centers in fiscal 2025

And Microsoft isn’t the only one that is ramping up its investments into AI-enabled data centers. Rival cloud service providers are all investing in either upgrading or opening new data centers to capture a larger chunk of business from developers and users of large language models (LLMs).  In a report published in October 2024, Bloomberg Intelligence estimated that demand for generative AI would push Microsoft, AWS, Google, Oracle, Meta, and Apple would between them devote $200 billion to capex in 2025, up from $110 billion in 2023. Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025. Both figures, though, are way higher than Microsoft’s 2020 capital expenditure of “just” $17.6 billion. The majority of the increased spending is tied to cloud services and the expansion of AI infrastructure needed to provide compute capacity for OpenAI workloads. Separately, last October Amazon CEO Andy Jassy said his company planned total capex spend of $75 billion in 2024 and even more in 2025, with much of it going to AWS, its cloud computing division.

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John Deere unveils more autonomous farm machines to address skill labor shortage

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Self-driving tractors might be the path to self-driving cars. John Deere has revealed a new line of autonomous machines and tech across agriculture, construction and commercial landscaping. The Moline, Illinois-based John Deere has been in business for 187 years, yet it’s been a regular as a non-tech company showing off technology at the big tech trade show in Las Vegas and is back at CES 2025 with more autonomous tractors and other vehicles. This is not something we usually cover, but John Deere has a lot of data that is interesting in the big picture of tech. The message from the company is that there aren’t enough skilled farm laborers to do the work that its customers need. It’s been a challenge for most of the last two decades, said Jahmy Hindman, CTO at John Deere, in a briefing. Much of the tech will come this fall and after that. He noted that the average farmer in the U.S. is over 58 and works 12 to 18 hours a day to grow food for us. And he said the American Farm Bureau Federation estimates there are roughly 2.4 million farm jobs that need to be filled annually; and the agricultural work force continues to shrink. (This is my hint to the anti-immigration crowd). John Deere’s autonomous 9RX Tractor. Farmers can oversee it using an app. While each of these industries experiences their own set of challenges, a commonality across all is skilled labor availability. In construction, about 80% percent of contractors struggle to find skilled labor. And in commercial landscaping, 86% of landscaping business owners can’t find labor to fill open positions, he said. “They have to figure out how to do

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2025 playbook for enterprise AI success, from agents to evals

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More 2025 is poised to be a pivotal year for enterprise AI. The past year has seen rapid innovation, and this year will see the same. This has made it more critical than ever to revisit your AI strategy to stay competitive and create value for your customers. From scaling AI agents to optimizing costs, here are the five critical areas enterprises should prioritize for their AI strategy this year. 1. Agents: the next generation of automation AI agents are no longer theoretical. In 2025, they’re indispensable tools for enterprises looking to streamline operations and enhance customer interactions. Unlike traditional software, agents powered by large language models (LLMs) can make nuanced decisions, navigate complex multi-step tasks, and integrate seamlessly with tools and APIs. At the start of 2024, agents were not ready for prime time, making frustrating mistakes like hallucinating URLs. They started getting better as frontier large language models themselves improved. “Let me put it this way,” said Sam Witteveen, cofounder of Red Dragon, a company that develops agents for companies, and that recently reviewed the 48 agents it built last year. “Interestingly, the ones that we built at the start of the year, a lot of those worked way better at the end of the year just because the models got better.” Witteveen shared this in the video podcast we filmed to discuss these five big trends in detail. Models are getting better and hallucinating less, and they’re also being trained to do agentic tasks. Another feature that the model providers are researching is a way to use the LLM as a judge, and as models get cheaper (something we’ll cover below), companies can use three or more models to

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OpenAI’s red teaming innovations define new essentials for security leaders in the AI era

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI has taken a more aggressive approach to red teaming than its AI competitors, demonstrating its security teams’ advanced capabilities in two areas: multi-step reinforcement and external red teaming. OpenAI recently released two papers that set a new competitive standard for improving the quality, reliability and safety of AI models in these two techniques and more. The first paper, “OpenAI’s Approach to External Red Teaming for AI Models and Systems,” reports that specialized teams outside the company have proven effective in uncovering vulnerabilities that might otherwise have made it into a released model because in-house testing techniques may have missed them. In the second paper, “Diverse and Effective Red Teaming with Auto-Generated Rewards and Multi-Step Reinforcement Learning,” OpenAI introduces an automated framework that relies on iterative reinforcement learning to generate a broad spectrum of novel, wide-ranging attacks. Going all-in on red teaming pays practical, competitive dividends It’s encouraging to see competitive intensity in red teaming growing among AI companies. When Anthropic released its AI red team guidelines in June of last year, it joined AI providers including Google, Microsoft, Nvidia, OpenAI, and even the U.S.’s National Institute of Standards and Technology (NIST), which all had released red teaming frameworks. Investing heavily in red teaming yields tangible benefits for security leaders in any organization. OpenAI’s paper on external red teaming provides a detailed analysis of how the company strives to create specialized external teams that include cybersecurity and subject matter experts. The goal is to see if knowledgeable external teams can defeat models’ security perimeters and find gaps in their security, biases and controls that prompt-based testing couldn’t find. What makes OpenAI’s recent papers noteworthy is how well they define using human-in-the-middle

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