Artificial intelligence has become a powerful tool for manufacturers.
The technology is allowing manufacturers to more quickly test new products and processes, as well as be more exact, efficient and safe in their operations. But to succeed in leveraging AI, companies need to know how best to integrate the technology into existing processes and how to make the tech work best for their specific needs.
Read more for how manufacturers are using AI to drive improvements in everything from drug manufacturing to employee safety, and what workers have to say about the adoption of the technology.
Gen Z workers say learning more AI tools will improve their value to employers
Nearly half of all workers feel they could lose out on job opportunities to those with better generative artificial intelligence skills.
By: Carolyn Crist• Published Feb. 21, 2024
About 43% of workers across generations are worried that another employee with better skills in generative artificial intelligence could replace them in their role in the next year, according to a Feb. 12, 2024 report from D2L, a learning technology company.
Generation Z workers appear to be most worried about this. While 52% of Gen Z workers said they’re worried about being replaced within the next year, 45% of millennials and 33% of Generation X workers said the same.
“What this new data suggests is that there’s an opportunity for employers to help workers better prepare themselves for the future and to give people the confidence that they can continue to make a meaningful contribution in their roles,” Sasha Thackaberry, vice president of Wave at D2L, said in a statement. “Skills development — whether it’s on using generative AI more efficiently or simply upskilling to stay ahead of change — is crucial for workers to keep up with the rapidly changing landscape of work.”
In a survey of 3,000 full-time and part-time U.S. employees, 60% said they want to use generative AI tools more frequently at work during the next year. About 49% said they’re already using AI tools at least once a week at work, and 52% said they’re using the tools outside of work. At the same time, 37% said they never use AI tools.
In preparation for the future workplace, younger workers were more likely to say they plan to take multiple professional development courses during the next year. About 26% of Gen Z workers and 24% of millennials said they plan to enroll in 6-10 courses in the next 12 months, as compared with 12% of Gen X workers.
Despite ongoing unease about AI in the workplace, worker confidence may be growing compared to previous years, according to a Robert Half report. HR and tech professionals, in particular, believe generative AI tools will create more demand for their skills.
However, mid-career professionals and managers (between ages 25-54) appear to be most at risk for generative AI disruption, according to an Indeed report. Many of these positions are considered “exposed” to disruption, where AI can perform a high percentage of the required skills in a “good” or “excellent” manner.
From an HR perspective, AI tools have the potential for “massive gains,” an HR software expert told HR Dive. AI can help with predictive text and scheduling functions, for instance, which may assist with talent acquisition. AI may also account for human bias and improve diversity and inclusion objectives, she said.
Article top image credit: miniseries via Getty Images
Samsung scores $6.4B in CHIPS funds
The money will aid the chipmaker’s Texas manufacturing construction plans and help create at least 21,500 jobs.
The chipmaker will use the funds to help build two logic fabrication plants, a research and development fab and an advanced packaging fab in Taylor, Texas. It will also expand its existing Austin, Texas, plant, bringing the company's total regional investment to over $40 billion.
The projects are expected to create at least 21,500 jobs, including 17,000 construction jobs and 4,500 manufacturing positions, according to the department. Samsung will also leverage $40 million in CHIPS funding on workforce development initiatives.
"These facilities will support the production of some of the most powerful chips in the world, which are essential to advanced technologies like artificial intelligence and will bolster U.S. national security," President Joe Biden said in a statement.
Samsung, which has been manufacturing semiconductors in Texas since 1996, produces both advanced memory and advanced logic technologies. The highly coveted chips power everything from smartphones to high performance computing and military AI solutions.
The South Korea-based company broke ground on its Taylor project in 2022 with an investment of $17 billion. It plans to start production this year, according to its website.
The logic foundry fabs will produce 4nm and 2nm process technologies, while the R&D facility will focus on technology generations ahead of nodes currently in production. The packaging plant will manufacture 3D high bandwidth memory and 2.5D packaging, key for AI applications.
Samsung's funds are part of a wider rollout in CHIPS money to leading semiconductor makers across the country. The Biden administration has doled out roughly $23 billion total in funds to power its promised renaissance in domestic semiconductor manufacturing.
In the era of intelligent manufacturing, the integration of AI and digital twin technologies heralds a new chapter of innovation and efficiency. Manufacturers should explore software solution vendors that are offering solutions that seamlessly meld with these advancements to unlock unprecedented operational efficiencies. IFS's comprehensive software suite does this and more, enabling manufacturers to navigate the complexities of modern production landscapes, driving forward with data-driven insights and real-time operational visibility.
Embracing the digital twin technology with advanced solutions enables manufacturers to create precise virtual replicas of their physical assets. This capability not only enhances predictive maintenance and operational planning but also serves as a testbed for innovation, allowing for the simulation of new processes and the optimization of existing ones. With IFS, companies can transcend traditional manufacturing boundaries, fostering a culture of continuous improvement and operational excellence.
AI: The Architect of Smart Manufacturing
The application of AI in manufacturing transforms the paradigms of production and supply chain management. By harnessing the predictive power of AI, businesses are empowered to anticipate market trends, optimize inventory levels and streamline production schedules, ensuring that they stay ahead in a competitive landscape. This predictive prowess is not just about responding to market demands but proactively shaping manufacturing strategies for maximum efficiency and customer satisfaction.
Moreover, IFS's solution intelligence extends beyond forecasting to enhance every facet of the manufacturing process. From optimizing resource allocation to ensuring the highest standards of product quality, IFS's technology stack leverages the latest innovations to make smart, data-informed decisions. This integration of AI and machine learning across operations simplifies complexities, reduces operational overheads and ensures that manufacturing outcomes align with strategic and specific processes and business goals, setting a new standard forsmart manufacturing.
Optimizing Every Facet of Manufacturing
AI's influence permeates through various facets of manufacturing, fromintricate schedulingto rigorous quality control. By harnessing AI-powered solutions, manufacturers can streamline complex production lines, ensuring that resources are judiciously allocated and production timelines are met with precision. Furthermore, AI-driven systems play a pivotal role in upholding stringent quality standards, employing advanced monitoring techniques and predictive analytics to preemptively address potential issues, thereby safeguarding the integrity of the manufacturing process.
Steering Towards a Greener Horizon
In this era where sustainability is paramount, AI stands as a pivotal ally in steering manufacturing towards greener practices. Enhancing process efficiency and reducing waste, AI aligns perfectly with the industry's environmental goals, ensuring resources are optimized and production processes are managed proactively. This shift towards eco-friendly operations gains further momentum with the EU's recent regulatory push for sustainability, specifically the Corporate Sustainability Reporting Directive, or CSRD. These regulations, aiming to establish a global benchmark, not only underscore the necessity of adopting sustainable practices but also highlight how AI's integration can facilitate compliance, drive efficiency and promote a more sustainable manufacturing landscape.
Embracing the AI-driven Future
For manufacturers poised to navigate this digital transformation, the journey entails a comprehensive embrace of AI technologies. The foundation of this journey lies in the recognition of quality data as the linchpin of informed decision-making and strategic innovation. By adopting a forward-looking approach and prioritizing areas with the highest potential for digital transformation one process at a time, manufacturers can unlock the full spectrum of benefits that advanced enterprise software technologies, like IFS, have to offer.
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Talent leaders grapple with embracing AI and work flexibility
Nearly all employers are planning “work design changes” for 2024, such as hybrid and return-to-office policies, a Mercer report stated.
By: Caroline Colvin• Published April 2, 2024
The global talent trends Mercer researchers have highlighted are the ones that have already made headlines: Inflation’s strain on workers’ wallets, their desire for more pay to keep up with the cost of living and the continued impact of AI. Employers and employees also still spar over new work models.
But, in a Feb. 29, 2024 webinar cracking open the report, Mercer’s Global Talent Advisory Leader Kate Bravery noted, “We've certainly got more uncertainty on the horizon. But at the same time, we've also seen greater convergence in views this year across generations and geographies.”
Here are a few key findings from Mercer’s report, which polled 12,200 HR professionals, as well as executives, employees and investors.
Artificial intelligence demands different human talent
A lot of the employers polled mentioned looking at AI as a matter of product integration. But generative AI is becoming a part of the fabric of work in general.
Mercer noted 20 priorities for HR leaders in 2024; no. 5 was “Redesigning work to incorporate AI and automation.” This means 40% of HR professionals polled by Mercer have AI workflows on their people agenda. (Also in the top 10 HR pro priorities were enhancing EX, improved health benefits, workforce planning and people analytics.)
In covering the report, Bravery noted the significance of the AI at work conversation. Referencing Mercer’s approach to researching humans in a “machine-augmented world,” Bravery said, “We know that it's humans [who] will effectively unlock AI’s real potential.”
More than 50% of executives polled by Mercer expressed their belief that their businesses won’t survive past 2030 without “embracing AI at scale.”
What are gold standard C-suites doing to successfully embrace AI? They prioritize human-centric productivity, foster trust, ensure equitable work practice and lean into a “digitally-infused future,” the report found.
“As risks become more connected and less predictable, [organizations that outpace their competitors] understand that a new level of risk awareness and mitigation is essential to building a ready and resilient workforce,” researchers said in the report.
As new work models emerge, EX should be re-examined
“I don't think you'll be surprised, but HR’s top concerns this year are rising labor costs, and ensuring new work models — flex, gig, short-term work models — are really delivering long-term value,” Bravery said.
A whopping 98% of employers are planning “work design changes” for 2024. The main goal is to tweak workflow to increase productivity; Mercer identified the concept of fixed roles, flex roles or “agile roles that benefit from skills-based planning and credentialing.”
Hybrid work continued to reign as a key factor in productivity. “While it may seem that employers have finalized return-to-office plans and codified their post-pandemic flexible working policies, in fact 41% are planning further changes this year,” researchers said in the report.
Mercer broke down flexible work into “six dimensions:”
Where, as in location and infrastructure;
When, as in hours and scheduling;
What, as in job content and sharing;
Who, as in alternative workforce and automation;
How, as in scaling and technology; and
Why, as in mission and purpose.
The idea of value was persistent across the webinar. For one, more workers said they were sticking with their employer this year — which is poignant, given that panelists acknowledged the Great Resignation and how it changed the work landscape.
Bravery also highlighted, “More employees shared that their needs are not being met — especially older workers and Gen Z. We've got work to do there.”
Engagement will be an area that stakeholders “need to watch out for this year,” across the board, Bravery said.
Manufacturers are using deals as a way to leverage new technology capabilities and diversify their supply chains.
By: Rebecca Heilweil• Published April 9, 2024
While the pace of mergers in the manufacturing industry seemed to decline last year, 2024 outlooks are optimistic about a rebound in dealmaking later this year.
Manufacturers have secured several high-profile acquisitions in recent months. In February 2024, Novo Holdings — the controlling shareholder behind Novo Nordisk, maker of the popular weight-loss drug Ozempic — bought the contract drugmaker Catalent for $16.5 billion. Similarly, Toyota announced in March 2024 its plan to purchase former Panasonic joint venture battery company Primearth EV Energy Co., in a bid to respond to electric vehicle demand.
Overall, 65% of industrial manufacturing C-suite executives said in a recent KPMG survey they expect dealmaking to increase this year, despite last year’s slowdown. Ultimately, several trends, including stabilizing economic indicators and the emergence of new technologies, could contribute to that growth, even as some barriers remain.
There’s less uncertainty in the broader market, which has made companies feel more empowered to consider acquisitions, said Michelle Ritchie, global industrial manufacturing and automotive deals leader at PwC. The supply chain is less volatile than it was during the pandemic, interest rates appear to have peaked and inflation seems to have normalized, she noted. For those reasons, executives might feel more ambitious about pursuing a deal in the coming year.
“What people came into 2024 feeling is less uncertainty,” Ritchie said. “All of those factors are going to set the rest of the year up for much more activity because people are going to get busy.”
Deals could focus on new technology
Companies are increasingly thinking about emerging technologies as they consider potential deals. This includes digital twin software, which enables simulations of manufacturing capacity, artificial intelligence-based applications and other digital assets.
“AI is all about predictions…You have to invest in your data quality. You have to invest in your IT platforms. And last but not least: you need certain process knowledge,” said Helmuth Ludwig, a professor of practice in strategy and entrepreneurship at Southern Methodist University. “Now, you might have great ideas, but how do you start?”
Acquisitions can help companies better expand their use of or access to digital technology, according to PwC. For the automotive industry in particular, acquisitions can help companies adapt to the rise of EVs. For example, last November Volvo bought electric bus manufacturer Proterra’s battery business to help the car company keep up with competitors like Tesla and General Motors.
Potential acquisitions face antitrust scrutiny
Regulatory review of mergers and acquisitions in many sectors, including manufacturing and technology, appears to have increased in recent years. This trend could impact how companies if, when and how companies pursue deals. While industrial policy investments from the Biden administration are accelerating activity in the manufacturing space, at least in the U.S., there’s a chance deals aren’t pursued because of regulatory concerns, Ritchie said.
“There's a lot of questioning, sometimes in the way early stages, of: do we want to do this acquisition [and] could we get it through regulatory approval?” said Ritchie. “If we can’t get it through regulatory approval, do we even embark on it? Which is not something we had heard in the past.”
Contract manufacturing deals could help diversify production
Global conflict has continued to make companies more interested in mergers and acquisitions that could bolster their supply chain stability and diversify their relationships with contract manufacturers.
For example, the impacts of the pandemic, along with surging tariffs, have made companies more interested in working with or acquiring companies that might provide manufacturing capacity outside of China, Ritchie noted. Now, more companies are interested in exploring manufacturing locations in Southeast Asia, India and Europe, such as in Poland, and discovering that they can be as affordable as options in China.
Strategic acquisitions and staying ahead
Despite the market shifts, some broad trends in manufacturing M&A activity remain the same, Ludwig said. This includes smaller companies looking to gain efficiencies through acquisitions — while other players use deals to diversify. But as the market continues to change, CEOs are likely to look at mergers and acquisitions as a way to stay ahead of a quickly evolving economy and keep their business relevant, Ritchie said.
And when approaching a new deal environment, she added that companies need to ensure they’re ready for the change interally.
“They need to position themselves to be successful in that new environment. So it's all the companies doing that, saying: Am I going to be ready? Am I going to be most efficient? Do I have the digital manufacturing to be able to be flexible?” Ritchie said. “What is it that I need to be able to operate competitively in that new environment?”
Article top image credit: Getty Images/Staff via Getty Images
Mercedes-Benz to pilot humanoid robots in its manufacturing facilities
The automaker plans to use the robots to perform physically demanding or repetitive tasks that are often more hazardous to humans.
By: Eric Waltz• Published March 21, 2024
Dive Brief:
Mercedes-Benz and robotics company Apptronik have agreed to deploy humanoid robots at the automaker’s manufacturing facilities, Apptronik announced March 15.
As part of the agreement, both companies will study the potential use cases for Apollo humanoid robots in logistics, such as delivering parts to assembly line workers.
The robots can help automate tasks that are physically demanding, repetitive or hazardous for humans. They can also address labor shortages by performing less desirable tasks.
Dive Insight:
Advances in robotics technology can help make workplaces safer for humans and increase efficiency. In January 2024, BMW announced a similar project at its manufacturing facilities in South Carolina. Tesla is also considering deploying its AI-powered, humanoid “Tesla Bot” in its factories to work alongside humans.
"Mercedes plans to use robotics and Apollo for automating some low skill, physically challenging, manual labor – a model use case which we'll see other organizations replicate in the months and years to come,” Apollo CEO Jeff Cardenas said in the press release.
Apptronik was founded in 2016. The company spun out of the Human Centered Robotics Lab at the University of Texas at Austin. The humanoid Apollo robot resulted from Apptronik’s experience building over 10 previous robots, including the Valkyrie robot for NASA.
The Apollo robot is around the size of a human worker, standing 5 foot 8 inches tall and weighing 160 pounds. It can lift objects weighing up to 55 pounds and work alongside humans in industrial settings, performing more physically demanding tasks in factories. The robot can operate with its onboard battery pack for up to four hours.
“This is a new frontier and we want to understand the potential both for robotics and automotive manufacturing to fill labor gaps in areas such as low skill, repetitive and physically demanding work and to free up our highly skilled team members on the line to build the world's most desirable cars,” Jörg Burzer, who’s in charge of the Production, Quality & Supply Chain Management division, said in the press release.
Article top image credit: Courtesy of Apptronik
How AI is changing drug manufacturing
How artificial intelligence is moving into pharmaceutical production and what the FDA is doing about it.
By: Deborah Abrams Kaplan• Published Nov. 8, 2023
On one filling line each day, Medivant Healthcare produces 20,000 single dose injectable vials. These vials end up at patient bedsides, on hospital crash carts and in the emergency room, often for patients needing an anesthetic.
The FDA requires that each vial be visually inspected before leaving the plant. Currently, Arizona-based Medivant uses humans to verify that there are no visible particulates or label defects that would render the vials unusable.
But soon, the company’s vial inspection machine will take over that process. “People get tired and bored,” and can miss some defects, while the machines do not, said Medivant CEO Viraj Gandhi.
As part of the machine’s AI training process, Medivant sets standards for what the banned particles look like, to use in the algorithm training, Gandhi added that AI is seeping into many parts of the drug manufacturing process, something the FDA is monitoring. Earlier this year, the agency released a discussion paper, Artificial Intelligence in Drug Manufacturing, requesting comments from stakeholders and the public on how the technology can be best used in the sector.
Integrating AI into drug manufacturing is difficult because the industry is highly regulated, said Thomas Hartman, president and CEO of the International Society for Pharmaceutical Engineering. Any process changes, including the direct or indirect introduction of AI, can impact product quality, requiring the manufacturer to go through a comprehensive change control procedure, which is time and resource intensive.
How drug manufacturing currently uses AI
In addition to quality control, AI can help manufacturers understand how to optimize production processes. AI algorithms can help companies understand how trends and facility temperatures can impact the manufacturing process, including the impact on product quality or yield, said Sue MarchantEVP of product at MasterControl, which sells software for quality management and manufacturing execution.
Some manufacturers use AI to focus on a single manufacturing step prior to commercialization, according to Marchant. During the R&D phase, they run through the manufacturing process changing one step at a time to determine if that improves the quality, results or efficiency.
AI can be used to augment a company’s visibility into operations, such as an unplanned deviation on the manufacturing floor. It can also provide contextual data, like sharing other times something similar happened at the facility and what caused it.
“We’re providing [workers] information to potentially guide their actions and assess risk,” Marchant said. “But we’re not yet prescriptively saying we believe you should take this action, so it’s just introducing AI into those processes in a very careful way.”
The technology can be integrated on the quality side, to make it easier for manufacturers to comply with regulations and ensure their practices are safe and secure, by reviewing data and highlighting at-risk areas, Marchant noted.
Challenges implementing AI in drug manufacturing
The biggest roadblock to implementing AI in drug manufacturing is cost, Gandhi said. Medivant spent millions of dollars on its semiautomatic vial inspection, which he says is 10 times more than the cost of human labor for the same job.
“Everyone wants to do this, but you need enough capital,” Gandhi said.
Medivant bought its machine four months ago and is training and validating it with sample vials for four to five months, then will test it with commercial batches. After putting it into production, the company will also perform manual observations for six to nine months, to ensure there are no false negatives in the inspections. Then it will become the manufacturer’s primary inspection method.
Investing in automation and AI is difficult for smaller manufacturing companies like Medivant, which makes generic, low-cost drugs like epinephrine and lidocaine. The company’s products mostly sell for dollars per vial, Gandhi said.
AI tools are, however, more widely adopted by larger manufacturers. “The big ones typically take a risk in new equipment and see how it goes,” Gandhi added.
Another limitation to adopting AI is having the appropriate digitized data available to train the algorithms and run the analyses. This can limit the AI options to larger players, Marchant said, as many smaller manufacturers still use paper logbooks or rely primarily on on-premise data storage, rather than cloud services.
Incorporating AI may require that the “entire manufacturing process is digital, you have outlined every step in your manufacturing process, you are capturing every step digitally, you’re capturing the date and time it occurred, who participated and what the parameters of each step were,” Marchant said. Manufacturers may also need to combine and accurately integrate data from disparate sources.
The FDA’s role
The FDA “has recognized and embraced the potential of advanced manufacturing to bring benefits to patients and consumers,” an agency spokesperson told Manufacturing Dive.
Its Center for Drug Evaluation and Research established the Emerging Technology Program in 2014 to work with stakeholders on supporting advanced manufacturing, including tech such as AI. CDER recognized that regulatory policies and programs may need to evolve to enable timely technology adoption, according to the spokesperson.
“A lot of what we’ve seen [from the FDA] is them trying to get a handle on it,” Marchant said. “There’s not a lot of strong guidance about what companies should do.”
The result, she said, is companies may be hesitant about using AI as they are uncertain what it will mean for them in the future.
“A lot of what we’ve seen [from the FDA] is them trying to get a handle on it. There’s not a lot of strong guidance about what companies should do.”
Sue Marchant
Executive VP of Product, MasterControl
Marchant said her customers are erring on the conservative side, asking in requests for proposals how AI is used in MasterControl software. They are concerned about whether future FDA requirements will interfere with their processes if they adopt AI tools now.
“Everyone’s sort of in a wait and see mode,” Marchant noted. “The FDA definitely wants to encourage innovation, because their message is that they’d like to embrace innovation, and yet what does that really mean? That’s what nobody really knows yet.”
The FDA is interested in incorporating AI in drug manufacturing and highlighted for Manufacturing Dive ways it could potentially improve the process:
• Identify optimal process design and scale-up strategies that might reduce development time and waste
• Gain greater control of product and process quality while reducing human involvement and human error
• Better monitor manufacturing processes and detect changes in performance that trigger preventative maintenance activities and reduce process downtime
• Prevent more process deviations, and in the case of a deviation allow for better root cause identification of the underlying problem
In addition to requesting feedback from stakeholders and the public, in September the FDA cohosted a workshop with the Product Quality Research Institute on the regulatory framework for the use of AI in drug manufacturing.
CDER’s goal, the spokesperson said, is to help patients realize the benefits of using AI in drug manufacturing, while minimizing risks, such as those stemming from the use of AI for unethical outcomes.
The biggest fear, Gandhi said, is that the data can be manipulated. On the inspection side, there is already stringent FDA regulation to validate the accuracy and security of the machine and inspection results.
Article top image credit: XH4D via Getty Images
Worker confidence in AI may be growing despite unease about the tech
HR and tech professionals believe generative AI will create more demand for their skills, according to Robert Half.
By: Laurel Kalser• Published Sept. 14, 2023
Dive Brief:
Employees may be warming up to generative AI: 4 in 10 of the more than 2,500 U.S. workers surveyed by consulting firm Robert Half believe the technology will have a positive effect on their career, the firm announced Aug. 22.
Attitudes differ by occupation, the May 2023 research found. About two-thirds, 63%, of technology professionals and more than half of HR professionals said generative AI will create more demand for their skills. Age group also plays a role, as 63% of Generation Z respondents and 57% of millennials are optimistic about AI’s benefits, compared to 30% of Generation X respondents and 21% of baby boomers.
Generative AI’s greatest benefit is automating time-consuming tasks, more than one-third of respondents said, while 30% said the technology increased efficiency and productivity. For now, “embracing generative AI in the workplace will require a clear set of guidelines and openness to its potential,” Trisha Plovie, Robert Half’s senior VP of future of work, said in a press release.
Dive Insight:
The Robert Half findings suggest employees may be becoming more comfortable with the integration of AI into the workplace, a departure from recent studies revealing widespread concern among U.S. adults that AI will take jobs from humans, including theirs.
Recent college grads have also expressed unease about AI, according to a Cengage Group report released in July. Hiring managers surveyed for the report confirmed that AI could replace some entry-level jobs, teams and skills.
However, many HR managers have already embraced the tech, according to Robert Half. A separate survey by the consulting firm found that HR managers said they were using generative AI to write job descriptions, find and screen candidates, and evaluate employee performance.
Managers in other industries have welcomed the technology as well, the firm’s research showed: Those in finance and accounting said they’re using generative AI to automate data entry, while managers in administrative and customer support said they were using it to analyze and categorize customer feedback.
Generative AI is also helping tech managers process large volumes of data to improve system performance, and managers in the marketing and creative sectors are using it to write copy for campaigns, social media and communications, Robert Half said.
Employees who know how to use generative AI platforms — including ChatGPT, BERT and Stable Diffusion — have reasons to be confident, a recent Upwork report found. Generative AI jobs were up more than 1,000% on the platform in the second quarter of 2023 compared to the end of 2022, Upwork said.
Article top image credit: Andrea Verdelli via Getty Images
Tesla installing $500M supercomputer to train AI at gigafactory
The New York facility’s Dojo supercomputer will process massive amounts of data to support Tesla’s autonomous driving program.
By: Eric Waltz• Published Feb. 5, 2024
Dive Brief:
Tesla is spending $500 million to install a Dojo supercomputer at its Riverbend Gigafactory in Buffalo, New York, Gov. Kathy Hochul said in a Jan. 26 press release.
Tesla’s Dojo supercomputer, which will be installed over the next five years, will be used to train its artificial intelligence systems that support autonomous driving.
The Dojo supercomputer is expected to be one of the most powerful computing platforms in the world, with the ability to train machine learning models and process millions of terabytes of data from Tesla’s electric vehicles.
Dive Insight:
The data processed by the Dojo supercomputer will help Tesla improve the safety and engineering of its Full Self Driving and Autopilot autonomous driving features and advanced driver assistance systems, according to the press release.
During Tesla’s Q2 2023 earnings call in July 2023, the company identified four main technology pillars required to enable vehicle autonomy at scale: large, real-world datasets; neural net training; vehicle hardware; and vehicle software. The Dojo supercomputer will support faster and cheaper neural net training for Tesla’s self-driving vehicles, according to the automaker.
“The better the neural net training capacity, the greater the opportunity for our Autopilot team to iterate on new solutions,” Tesla wrote in its Q2 2023 earnings presentation.
In September 2023, Morgan Stanley analysts led by Adam Jonas wrote in a note that Tesla’s Dojo supercomputer could boost the electric automaker’s market value by $600 billion by supporting AI-powered robotaxis, vehicle software, and advanced computer vision processing, according to a Reuters report.
Dojo can open up new addressable markets that "extend well beyond selling vehicles at a fixed price," the analysts wrote. "If Dojo can help make cars 'see' and 'react,' what other markets could open up? Think of any device at the edge with a camera that makes real-time decisions based on its visual field."
In December 2023, Bloomberg reported that Tesla’s Dojo project leader Ganesh Venkataramanan departed the company. Former Apple Inc. executive and Tesla director Peter Bannon leads the project now.
Article top image credit: Courtesy of Office of New York Governor Kathy Hochul
The growing use case for AI in manufacturing
AI is allowing manufacturers to more quickly test new products and processes, as well as be more exact, efficient and safe in their operations. But to succeed in leveraging AI, companies need to know how best to integrate the technology into existing processes.
included in this trendline
Mercedes-Benz to pilot humanoid robots in its manufacturing facilities
Tesla installing $500M supercomputer to train AI at gigafactory
Gen Z workers say learning more AI tools will improve their value to employers
Our Trendlines go deep on the biggest trends. These special reports, produced by our team of award-winning journalists, help business leaders understand how their industries are changing.