Transcript Highlights:

• Um, and data centers and the use of AI generally, of course, takes electricity.
• Um, and data centers and the use of AI generally, of course, takes electricity.
• Um and data centers and the use centers.
• And if you walk it backwards, as I say, AI goes back to data centers, goes back to energy.
• I mean, at some point, as we get more efficient, AI helps us to make better use of data centers.

Keywords: 958, all

Summary: The Intelligence Task Force met with a quorum present and approved the minutes from the August 14 meeting. The first presentation was from the National Retail Federation on artificial intelligence in the retail sector. NRF described AI use cases in three areas: consumer-facing tools such as chatbots, product descriptions, and marketing; employee-facing tools such as company-specific apps trained on employee manuals; and internal uses such as supply chain forecasting, inventory planning, fraud detection, cybersecurity, and coding support. The presenters said retail has been among the top deployers of AI and emphasized that the goal is to improve both customer and employee experience. NRF also outlined its principles for responsible AI use, organized around governance and risk management, customer engagement and trust, workforce applications, and business partner accountability. The group said retailers should maintain strong internal oversight, be transparent with customers, ensure compliance with existing laws, closely review workforce-related uses because they can be high-risk, and clearly define responsibilities between retailers and third-party developers. In policy discussion, NRF urged a tiered approach focused first on high-risk uses such as hiring, health care, financial, mortgage, and rental decisions, warned against fragmented rules that could favor only the largest firms, and encouraged voluntary standards and worker upskilling incentives. In response to a question about dynamic pricing, NRF said its members do not target consumers based on pricing and offered to follow up with more information. The committee then moved to a follow-up discussion on energy policy and data centers, hearing from Bartley Cleland of NetChoice. He explained that AI runs largely in data centers and that cloud computing shifts processing and storage away from individual devices, which he argued improves efficiency and can reduce costs. He said electricity demand has been rising over time and that AI will increase compute-related electricity use, but framed electricity as a normal input to economic growth. No votes or formal actions were taken after these presentations.

Transcript Highlights:

• FIRST WE WILL HEAR FROM THREE PERSPECTIVES OF HOW THE DATA CENTERS THAT POWER AI MAY IMPACT ENERGY INFRASTRUCTURE
• YOU SPOKE MOSTLY ABOUT THE MEGA DATA CENTERS AND THE VERY LARGE AI DATA CENTERS AND THEY ARE ALSO SMALLER
• TO THE EDGE DATA CENTERS.
• IN MANY WAYS DATA CENTERS AND AI ARE ALREADY PART OF THE REASON FPL CAN MAINTAIN STRONG RELIABILITY AND
• SO YOU ARE SAYING IN THE AI DATA CENTERS THAT WILL NOT HAPPEN. >> THAT IS CORRECT.

Transcript Highlights:

• data and AI literacy Workforce uh around data and AI literacy um<01:09:21.000> and<01:09:21.239
• a data center in around my a data center in around my area<01:14:09.560> and<01:14:09.760>
• <01:14:51.480> centers water is used to cool the data centers water is used to cool the data
• their data center strategically locating their data center in<01:16:27.920> an<01:16:28.120><
• <01:29:36.560> centers talking about the big uh data centers talking about the big uh data

Keywords: 1187, senate, all

Transcript Highlights:

• it has ever been, because AI tools are getting to where they are because of data, that we are working
• Assemblymember Bauer-Kahan, you pointed out that AI learns from data created by humans, and those data
• And with that data set, we can train an AI system that goes from the device data from this tiny little
• Do we see that being robustly done when AI companies come in asking for that patient data?
• data exchange, and it's potential that we need to copy one of those models for AI.

Summary: The joint informational hearing of the Assembly Health and Privacy Committees focused on generative AI in health care, with opening remarks emphasizing both its potential to improve care and its risks around privacy, bias, liability, workforce impacts, and unequal access. Chair Bauer-Kahan and Chair Bonta framed the discussion around how California can encourage beneficial innovation while protecting patients, especially given the sensitivity of health data and the possibility that AI could worsen existing disparities if not carefully governed. The first panel featured representatives from Cedars-Sinai, Kaiser Permanente, Penguin AI, and Google, who described current uses of AI such as ambient clinical scribes, nursing documentation tools, imaging triage, maternal-fetal risk prediction, and administrative automation. Speakers said these tools can reduce clinician burden, improve patient experience, speed treatment, and in some cases improve outcomes, including a reported mortality benefit from a Kaiser predictive model and faster thrombectomy times at Cedars-Sinai. Members raised concerns about accuracy with accents and multilingual visits, whether predictive tools could reinforce bias or lead to more interventions such as C-sections, and how to ensure a human remains in the loop for important decisions. The second panel, including representatives from the California Health Care Foundation, UC Berkeley, and Stanford, focused on policy and governance challenges. Testimony highlighted examples of AI supporting homelessness outreach and community health work, but also warned that biased algorithms can encode inequities, especially when trained on data that reflect under-treatment of Black, rural, or low-income patients. Witnesses urged clearer standards for trustworthy AI, stronger monitoring and governance structures, better data access for accountability, and attention to the safety net’s limited resources. Several speakers argued that states should require health systems to have AI governance processes, clarify liability between developers and deployers, and regulate downstream uses of AI while preserving access to data for lifesaving research and oversight.

Transcript Highlights:

• Privacy: AI has created the next gold rush, and that gold rush is for our data.
• The CSU AI license further safeguards data, guaranteeing that no CSU data, prompts, or responses will
• an M.S. in AI and an M.S. in Applied Data Intelligence.
• with a focus on responsible AI, aligning with the newly launched human-centered AI certificate, our
• Data centers now account for more than 4% of U.S. electricity usage.

Summary: The Assembly Committee on Higher Education and the Assembly Privacy and Consumer Protection Committee held an oversight hearing on the California State University’s AI-empowered initiative, including the systemwide rollout of ChatGPT EDU and broader AI integration across CSU campuses. Opening remarks emphasized both the promise of AI for student success, workforce preparation, and access, and the need to address risks such as bias, privacy, misinformation, environmental impacts, and mental health harms. CSU representatives said the initiative grew out of Academic Senate recommendations and a systemwide generative AI committee, and that the goal was to provide equitable access, training, governance, and workforce alignment across the 23-campus system. CSU officials described systemwide contracts for AI tools, the AI Commons training hub, and faculty grant programs supporting AI-related curriculum innovation. They said more than 93,000 ChatGPT EDU accounts had been activated, over 4,300 faculty had taken voluntary training, and $3 million had been awarded to 63 faculty-led projects from more than 400 submissions. San Jose State University highlighted its own AI-focused programs, courses, orientation training, faculty fellows, student ambassadors, and interdisciplinary efforts to build AI literacy and responsible use into instruction and co-curricular programs. CSU also said it was tracking metrics on adoption, academic outcomes, workforce outcomes, and environmental impacts. Faculty, staff, and student representatives welcomed the educational potential of AI but raised concerns about the rollout, saying it had moved quickly and without enough consultation or consistent systemwide policy. They urged stronger protections for academic freedom, intellectual property, privacy, equity, and worker input, and warned about bias, surveillance, job displacement, and the environmental cost of AI. Legislators pressed CSU and OpenAI representatives on training requirements, data privacy, bias reporting, discipline for misuse, liability, sycophancy, and safeguards against harmful uses such as non-consensual imagery or self-harm-related interactions. CSU said interactions in the licensed tool are private, data are not used to train models, and campuses retain their own conduct processes; members also asked CSU to follow up on systemwide training, policy consistency, and additional safeguards.

Transcript Highlights:

• Health Center.
• The lenses that we use there are really focused on data security and ethical use of AI for these individuals
• A UW-wide center housed in the school that focuses on responsibility in AI systems and experiences.
• and then use AI as an assistive technology and then develop AI tools.
• So not just use AI, but think about using AI.

Summary: The committee spent much of the meeting hearing presentations on student mental health supports at Central Washington University, Washington State University, the University of Washington, and the State Board of Community and Technical Colleges. CWU described high levels of student distress, loneliness, anxiety, depression, suicidal ideation, and basic-needs insecurity, along with a campus-wide holistic well-being model that includes behavioral intervention teams, emergency aid, peer outreach, community partnerships, and a collegiate recovery community. WSU emphasized loneliness, common presenting concerns such as anxiety, depression, PTSD, and relationship distress, and the role of housing and residence life, resident advisors, living-learning communities, and coordinated crisis response in identifying and supporting students. UW highlighted prevention and support programs through LiveWell, including alcohol and other drug consultations, confidential advocacy, suicide intervention, student needs navigation, peer health educators, and peer wellness coaches. The community and technical college system reported persistent access barriers, especially for students ages 18 to 24 and those facing housing or food insecurity, and said the legislature-funded mental health pilot at four colleges expanded counseling access, telehealth, and referral pathways, while broader system efforts focus on awareness, telehealth, basic-needs supports, and workforce training in behavioral health fields. Members asked each panel how they gather student feedback, and the institutions said they use surveys, evaluations, and ongoing outreach to students in services. Questions also focused on substance-use and recovery resources, Greek life outreach, and whether colleges have enough licensed mental health staff versus academic advisors; the community college board said not all colleges have licensed mental health providers on staff, and some rely on community contracts or telehealth. The committee also discussed whether counseling services are increasing because of post-pandemic effects or because students are more willing to seek help, with presenters saying both factors likely play a role. The committee then shifted to artificial intelligence in higher education. Washington State University, the University of Washington, Western Washington University, and the community and technical college system described campus AI task forces, governance structures, and efforts to set policies for students, faculty, and staff. Presenters said institutions are requiring course-level AI use statements, promoting ethical and transparent use, expanding access to approved tools such as Microsoft Copilot, and using AI for teaching, research, advising, and administrative support while guarding privacy, equity, and academic integrity. Members raised concerns about deepfakes, bias, student monitoring, and whether AI should be used to screen applications or evaluate student work; presenters said human review remains essential and that some institutions prohibit AI use in hiring or admissions screening. The final presentation, from OSPI, described the statewide rollout of the School Links high school and beyond plan platform under 2023 legislation, saying it will standardize career and college planning across K-12, provide better data and student guidance, and connect students to postsecondary pathways and employers; OSPI said the rollout is underway but current funding only extends through June 30, 2026.

Transcript Highlights:

• Uh, that will transition us into how that relates to AI and cloud data center and site selection process
• into how that relates to AI and cloud uh<00:03:11.519> data<00:03:11.840> center<00:03:
• data center and AI transition into the data center and AI component<00:09:52.720> of<00:09:52.880
• Data centers have to be located if it's a large data center.
• see AI data center investments, going to see AI data center investments, eclipse<00:45:09.680> office

Keywords: 958, all

Summary: The Artificial Intelligence Task Force held its third meeting and adopted the prior minutes after a motion and second. The main presentation came from John Bevington of LG&E and KU, who described the utility’s Kentucky service territory, its vertically integrated operations, and its role in economic development. He said the company supported 76 projects in 2024, representing about $3 billion in announced investment and roughly 3,000 jobs, and noted that about 45% of statewide investment announcements were in its service area. He also outlined a large project pipeline of about 8.5 gigawatts, with data centers making up roughly two-thirds of that interest. Bevington explained that data center siting differs from traditional manufacturing site selection because it is driven primarily by transmission access and grid capacity rather than a process of eliminating locations. He said large data centers must locate near transmission lines, that utilities must conduct formal studies to ensure existing customers are not harmed, and that the buildout timeline for utility infrastructure is much longer than for data centers. He cited a Deloitte study and other industry data to argue that power constraints and timeline mismatches are the biggest challenges, while also emphasizing that data centers can generate significant construction activity, indirect jobs, and tax revenue. He said Kentucky’s sales tax exemption for data centers was a key enabler that increased interest in the state. Members asked about the number and size of potential data center projects, how Kentucky compares with other states, and whether regulatory reform is needed. Bevington said the 20 projects in Kentucky reflect current interest, that other states such as Ohio have had similar incentives for years, and that Kentucky is still early in the market. He also said data centers can vary in size, from 200 to 600 megawatts or more, and that they can be located anywhere with sufficient transmission capacity and, in some cases, access to workforce and roads. In response to concerns about energy supply, he said LG&E and KU are pursuing an “all of the above” strategy, including solar, batteries, and new natural gas combined-cycle units, and noted ongoing and proposed projects totaling additional capacity if approved by the Public Service Commission.

Transcript Highlights:

• after data center after data center after data center.
• It's just data center on data center on data center on data center.
• It's stacked and they're actually concentrated in a fairly small. on data center on data center on data
• GDP in the last couple of years is accounted for by AI infrastructure and data center buildouts.
• How many data center campuses does that represent, that line for data centers?

Keywords: 907, all

Summary: The committee held a series of informational briefings on information management and technology issues. It first heard from ACLU representatives on data privacy, who argued that Oregon should strengthen protections against private data brokers, government purchases of personal data, reverse warrants, automatic license plate readers, and local police surveillance. They urged data minimization, limits on data sales and retention, and broader transparency and accountability measures. Members asked about practical uses of license plate readers, state sales of data, and how Oregon’s approach compares with other states; the presenters said similar proposals have been adopted elsewhere, including data minimization in Maryland and a state version of the Fourth Amendment Is Not for Sale Act in Montana. The committee then received a detailed update from the Department of Administrative Services and Enterprise Information Services on licensing system modernization for 14 boards and commissions with the most immediate need. DAS said it is seeking a shared procurement approach through an RFP that would create either one scalable system or two tiers of systems, depending on agency needs and security requirements, with contracts expected by September. Committee members emphasized the need for a more unified, user-friendly statewide login and service experience for businesses and residents, and raised concerns about small agencies “figuring it out on their own” without sufficient cybersecurity or technical expertise. EIS said it is overseeing the investment review, security and architecture review, and future implementation planning, and noted that multiple agency requests may still come back to the legislature in the next session. The committee also discussed a revised cybersecurity incident notification concept. Staff explained that the earlier bill had raised stakeholder concerns, so the co-chairs directed further interim work with the Oregon Cybersecurity Advisory Council and other local government and K-12 stakeholders. The goal is a narrower, voluntary “911-style” notification process that would let public bodies alert peers and potentially receive assistance after cyber incidents; a temporary voluntary process is being tested now, with a work group developing language for possible 2027 consideration. Finally, the committee heard updates from the new state chief data officer on data governance, data sharing, geospatial work, and the state transparency website, followed by a briefing on data centers from NCSL and the Technology Association of Oregon. The data officer described efforts to expand data inventories, data governance plans, data literacy, and interagency sharing, along with statewide aerial imagery, geospatial standards, and the open data portal. The data center discussion focused on national and state trends, including rapid growth in data centers, rising electricity and water demand, and legislative responses such as new rate classes, reporting requirements, and cost-allocation rules to protect ratepayers. No votes were taken; the meeting was informational only.

Transcript Highlights:

• If you don't have the right data, your AI is going to be absolutely ineffective.
• One area that we have perceived, like AI is creating a lot of jobs, actually it's not; it's data centers
• While we all say we will be green data centers, we're going to focus on green.
• You need to know your Data. You need to know what answers you want from AI.
• For a data center, however, those data centers, with the emergence of quantum, could be, who don't need

Transcript Highlights:

• It's a blockchain somewhere hidden in a data center. Like, I just don't get it.
• It's a blockchain somewhere hidden in a data center. Like, I just don't get it.
• The primary effect of classifying data as sensitive data is that it changes that data from being data
• The primary effect of classifying data as sensitive data is that it changes that data from being data
• about data practices and data privacy. about data practices and data privacy.

Bills: HF3642, HF2700, HF3615

Keywords: virtual currency, kiosks, prohibition, customer payouts, cryptocurrency regulation, consumer privacy, data privacy, health data, sensitive data, Minnesota Consumer Data Privacy Act, personal data, data broker, targeted advertising, geofencing, location tracking, health care privacy, patient privacy, consent, minor privacy, children's privacy

Summary: The Commerce Finance and Policy Committee met on House File 3642, which would prohibit virtual currency kiosks in Minnesota. The bill was laid over, and the committee adopted a DE1 author’s amendment. Chair Kaggel and Representative Perryman described the measure as a response to widespread scams using crypto kiosks, especially against older adults and other vulnerable people, and said they would continue working with the Department of Commerce and other stakeholders. Testimony from law enforcement and advocates strongly supported the ban. A St. Cloud police sergeant and a Woodbury detective described cases in which victims lost large sums, said the current safeguards and refund rules are being bypassed, and argued that the kiosks are difficult to investigate because funds move quickly and often overseas. An AARP Minnesota volunteer also supported the bill, saying kiosks are a preferred tool for scammers and that existing protections have not kept pace with the problem. The Department of Commerce said it strongly supports the bill and reported that it has received 120 complaints over three years involving nearly $1 million in reported losses, with 2025 the worst year so far. The main opposition came from CoinFlip’s general counsel, who argued that the problem is fraud generally, not kiosks themselves, and said Minnesota already has consumer protections, including refunds for eligible victims. He urged stronger regulation rather than a ban, citing blockchain analytics, hold periods, and 24-hour customer service as alternatives. Committee members then asked questions about how long kiosks have operated in Minnesota, how many there are, who owns them, and the scale of losses; Commerce said there are hundreds statewide, operated by a variety of companies, and that reported losses are likely undercounts.

Transcript Highlights:

• Um, obviously, data centers are needed to, you know, generate AI, particularly generative AI.
• Um, obviously, data centers are needed to, you know, generate AI, particularly generative AI.
• <01:27:45.920> centers<01:27:46.360> is what AI and not just data centers is what AI
• There may, just like data centers, be better ways to plan for AI.
• There may, just like data centers, be better ways to plan for AI.

Keywords: 1187, senate, all

Transcript Highlights:

• So we came up with the AI-centered guidance, which is to... Thank you.
• Guidance, which is to have the AI in the center of that.
• G.A.I., generative AI. And so our ability to utilize these data sets...
• Generative AI. And so our ability to utilize these data sets.
• How many data, you've, I think that they've built four or five data centers in Quincy, in and around

Summary: The committee met to hear an overview of Washington’s alternative learning experience (ALE) programs and then an update on artificial intelligence in schools. OSPI’s Anissa Sherritt explained that ALE is a course-level funding designation for instruction that occurs partly or wholly away from the traditional seat-time model, with online, site-based, and remote course types. She emphasized that ALE is still basic education, subject to the same public school requirements, and that OSPI provides technical assistance, annual reporting review, and program reviews. Representatives from several programs described different models: Washington Virtual Academy (a large online ALE operated through Omak School District and partnered with for-profit Stride), Columbia Virtual Academy in Valley School District (a district-run, nonprofit online/remote program), Pearl in Quilcene (a K-8 remote parent partnership program), and River Home Link in Battleground (a site-based hybrid program). They discussed student supports, special education, enrichment, family choice, transportation, and how they measure outcomes. Members asked for follow-up information on funding, demographics, racial and ethnic data, multilingual learners, and post-graduation outcomes, and OSPI agreed to provide additional data where available. The committee then heard from OSPI and several districts about AI guidance and implementation. OSPI’s Holly Ryan Calloway described the agency’s human-centered AI framework, three guidance documents for schools, statewide professional learning, an AI innovation summit, and new AI literacy and informatics course frameworks and CIP codes. Quincy School District described a multi-year effort to integrate AI by centering student needs, creating district policy and classroom guidance, and training teachers to use AI responsibly while building an AI readiness plan from elementary through high school. Peninsula School District described its AI action research team, teacher professional learning, and classroom uses of generative AI to support science instruction, communication, and prompt engineering, while stressing that AI should enhance rather than replace learning. Members raised questions about privacy, energy and water use, prompt engineering, workforce and university connections, and the need for clear standards and ongoing educator training. No votes were taken.

Transcript Highlights:

• We have a $4 to $10 billion data center being built in West Memphis.
• We have another $6 billion data center being built here in Little Rock, and within the next few years
• are going to have another two to three data centers being built.
• This really places the ethical and responsible use of AI tools at center stage.
• Amy Hawkins, and she's done a really good job creating an almost like AI learning center.

Summary: The meeting began with a report on institutions of higher education for annual certification/solvency, which required no action and was noted as coming later in the week. The main presentation featured students from Arkansas State University, Valley View High School, and the University of Central Arkansas discussing artificial intelligence in education and the workforce. They argued that AI should be taught responsibly in K-12 and higher education to prepare students for jobs, support Arkansas’s growing tech sector, and reduce misuse such as cybercrime, scams, plagiarism, and academic dishonesty. They also cited survey results from teachers showing broad support for responsible AI instruction, district-level management, and teacher training, while noting concerns about critical thinking, ethics, and unequal access. Examples were given of AI already being used at UCA and the University of the Ozarks, and the group suggested a statewide AI library and related training built on the Access Act framework. Committee members asked about student reactions, and the presenters said responses are mixed, especially in the arts, but that AI is already being used in real-world careers and should be integrated with clear standards. The committee then heard from a Pine Bluff community coalition led by Pastor Jesse Turner about school-based outreach and youth support programs. The group described long-running work in Pine Bluff schools and Watson Chapel, including Pass on Patrol, mentoring, anti-bullying and nonviolence efforts, drug and vaping education, gun-violence prevention, and leadership clubs for students. They emphasized that their approach is nonreligious in the schools, focused on encouragement, citizenship, scholarship, and keeping students engaged in class. They also highlighted the use of free curriculum resources on African American history and said they help students see themselves as having promise rather than being “at risk.” Members asked about whether the programs could be shared elsewhere and about impacts on behavior; the group said some materials are trademarked but can be adapted with support, and cited reported reductions in negative behavior and referrals in participating schools. The meeting ended after members praised both the AI presenters and the Pine Bluff outreach group, and the committee adjourned with no votes taken.

Transcript Highlights:

• Can you just briefly describe the interaction and how important it is if data centers are with AI for
• AI if it is data centers are with AI if it is data centers are with AI for<01:14:42.800> us
• Um, I think we're all concerned about the energy usage that some AI systems and data centers have.
• But data centers, they're critical for what a lot of these larger AI models.
• AI systems and data centers um have. AI systems and data centers um have.

Keywords: 1187, senate, all

Transcript Highlights:

• There's a number of other proposals to build additional data centers in Minnesota, and they already exist
• have also the data centers um that have also the data centers um that have popped<00:02:34.680>
• other proposals to build additional data other proposals to build additional data centers<00:02:
• data centers and some capital are the data centers and some senators<00:08:33.640> and<00:08:33.959
• data center is very that so right now data center is very hot<00:09:17.519> hotly<00:09:17.839

Keywords: 1187, senate, all

Transcript Highlights:

• We have a $4 to $10 billion data center being built in West Memphis.
• We have another $6 billion data center being built here in Little Rock, and within the next few years
• we're going to have another two to three data centers being built.
• This really places the ethical and responsible use of AI tools center stage.
• Amy Hawkins, and she's done a really good job creating an almost like AI learning center.

Summary: The meeting opened with a report on annual solvency certification for institutions of higher education, which required no action and was to be distributed later. The main presentation focused on artificial intelligence in K-12 and higher education, delivered by students from Arkansas State University, the University of Central Arkansas, and Valley View High School. They argued that AI is becoming central to education and the workforce, especially as Arkansas adds major data center investments, and said students should be taught to use AI responsibly so they can compete for jobs, improve internships, and keep talent in-state. They also emphasized concerns about academic integrity, cybercrime, and the need for ethics training and district-level guidance. The presenters shared survey findings from educators in several Arkansas districts, saying most teachers support teaching responsible AI use, believe students without access to AI will be disadvantaged, and want training and district-level management. They described existing AI uses at Arkansas colleges, including AI tutors, AI-generated practice exams, homework feedback tools, and classroom applications in business, climate science, and urban forestry. They also proposed an AI library built on the state’s Access Act infrastructure so K-12 and college students could access shared AI tools and resources across Arkansas. Committee members asked about student attitudes, classroom concerns, and whether AI could help standardize course materials and objectives across institutions. The presenters said reactions among students are mixed, with arts students especially worried about copyright and originality, but that many recognize AI’s real-world value. A UCA representative added that faculty training, ethics discussions, and academic dishonesty guidance are already underway there. The chair thanked the students, noted their work on related research projects, and then moved to a second presentation from Pine Bluff community leaders. The Pine Bluff group described community-based school support efforts, including the Pastors on Patrol program, mentoring, anti-bullying and nonviolence training, drug and vaping education, leadership clubs, and a youth diversion effort for students at risk of detention. They said their work is aimed at improving school climate, encouraging citizenship and scholarship, and reducing negative behavior. Members praised the group’s efforts and asked about expanding the programs to other districts; the presenters said their model and curriculum can be shared and adapted. The meeting ended after the chair thanked both groups and adjourned with no further business.

Transcript Highlights:

• That project helped open the West Texas market for AI data centers.
• I doubt there's actually an up and operational AI specific data center.
• There will be AI compute in a data center but it won't be exclusively dedicated to AI. Mr.
• So there are AI applications happening within data centers. We are not doing crypto and AI and...
• data centers?

Keywords: 1184, house, all

Transcript Highlights:

• HOW DO WE DEAL WITH SUCH AS THE ATTORNEY ASKED AI HOW WITH THIS CASE AND HE ASKED FOR DATA AND IT GAVE
• THAT IS FROM OUR PERSPECTIVE A MICROCOSM OF AI. THE CENTER OF GRAVITY FOR AI IS INDUSTRIAL AI.
• THESE NEW TECHNOLOGIES ARE BRINGING THOUSANDS OF TERABYTES OF DATA TO THE IN INDUSTRIAL AI IT NEEDS TO
• BECAUSE YOU HAVE TO BUILD A DATA PILED TO START OUR TRAINING AI TOOL.
• WHILE SOME ROLLS WILL BE DISPLACED AT NEW EMERGING IN AI DEVELOPMENT, DATA GOVERNANCE, HUMAN AI COLLABORATION

Transcript Highlights:

• THAT'S WHAT WE DO HERE IS NOT TO LEVERAGE AI OR TEACH OUR STUDENTS ALL ABOUT AI AND FORGET ABOUT THE
• BEYOND THE TWO WORDS AI.
• THERE IS ALSO AI TECHNOLOGY THAT IS NOW BEING OFFERED TO MANAGE CALL CENTERS, THEY HANDLE BUSINESS FUNCTIONS
• AI CAN AUTOMATE THAT BY PULLING THE NECESSARY DATA FROM FAX DOCUMENTS IN REAL-TIME AND IN ONE HEALTH
• WE NEED TO KNOW ONE OF THE DATA THAT ARE USED TO GENERATE THE PREDICTED AI MODELS.

Transcript Highlights:

• use of AI, setting a public model for responsible, worker-centered AI adoption that could extend into
• 00:09:53.120> AI model for responsible worker centered AI model for responsible worker centered
• <00:20:55.960> used<00:20:56.280> as call centers where AI is being used as call centers
• And then it comes into the need of, you know, data centers, which is something that I've been talking
• something know data centers which is something know data centers which is something that<00:35:57.200

Keywords: 1187, senate, all