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Web14/12/ · As IT complexity rises, so does the value of IT operations management (ITOM) Join us for a live discussion on November 15th- Register Now! Web21/10/ · A footnote in Microsoft's submission to the UK's Competition and Markets Authority (CMA) has let slip the reason behind Call of Duty's absence from the Xbox Game Pass library: Sony and Web12/10/ · Microsoft pleaded for its deal on the day of the Phase 2 decision last month, but now the gloves are well and truly off. Microsoft describes the CMA’s concerns as “misplaced” and says that Web26/10/ · Key Findings. California voters have now received their mail ballots, and the November 8 general election has entered its final stage. Amid rising prices and economic uncertainty—as well as deep partisan divisions over social and political issues—Californians are processing a great deal of information to help them choose state constitutional WebBlackBerry will be taking steps to decommission the legacy services for BlackBerry OS and earlier, BlackBerry 10 software, BlackBerry PlayBook OS and earlier versions, with an end of life or termination date of January 4, ... read more

Bulletin Board System. Blind Carbon Copy dt. Blindkopie, Feld im Kopf einer E-Mail, das zusätzliche Adressaten enthält, die aber nicht den anderen Adressaten mitgeteilt werden oder. Block Check Character dt.

Binary Coded Decimal. Basic Combined Programming Language. Backup Domain Controller oder. Business Data Catalog im Microsoft Office SharePoint Server. Binary Decision Diagram. Bit Error Rate Test Bitfehlerratentest. Bidirectional Forwarding Detection. Border Gateway Protocol. Bidirectional Text Layout, siehe Bidirektionaler Text. Bayonet Neill Concelman, siehe BNC-Steckverbinder. Bastard Operator From Hell. Base Operating System dt. Business Process Execution Language.

Binary Synchronous Communication. Berkeley Software Distribution. Blue Screen of Death. Computer Aided Architectural Design Computergestütztes architektonisches Planen und Entwerfen. Computer-aided engineering. Composite Application Framework. Computer-aided manufacturing. Controller Area Network oder. Content Addressable Network. Common ISDN Application Programming Interface.

Control And Provisioning of Wireless Access Points. Common Address Redundancy Protocol. Column Address Strobe: Dynamic Random Access Memory CAS. Catalog Service. Constant Angular Velocity. Cave Automatic Virtual Environment. Computer-Aided Woodcut zu Deutsch rechnerunterstützter Holzschnitt.

Camera Control Unit. Connected Device Configuration. Common Desktop Environment. Code Division Multiple Access. Content Delivery Network. Compact Disc Read-Only Memory. Conférence Européenne des Administrations des Postes et des Télécommunications. Control-flow Enforcement Technology.

Communicating Finite State Machines. Color Graphics Adapter. Common Gateway Interface. Challenge Handshake Authentication Protocol. Customer Information Control System. Classless Inter-Domain Routing. Common Intermediate Format. Common Internet File System. Computer-integrated manufacturing oder. Common Information Model. Complex Instruction Set Computer. Connected Limited Device Configuration. Call Level Interface oder. Command Line Interpreter oder.

Common Language Infrastructure. Character Large Object. Certificate Lifecycle Manager. Common Language Runtime. Connectionless Transport Service, ein verbindungsloser Service, beispielsweise UDP. Constant Linear Velocity. Capability Maturity Model oder. Color Management Module. Complementary Metal Oxide Semiconductor dt. Komplementärer Metall-Oxid-Halbleiter. Cyan Magenta Yellow Key, siehe CMYK-Farbmodell. Callable Object. Conference on Data Systems Languages.

Component Object Model oder. Common Object Request Broker Architecture. Connection Oriented Transport Service, ein verbindungsorientierter Service, wie beispielsweise TCP oder. Commercial off-the-shelf. Copy-On-Write , Verfahren zur Vermeidung von überflüssigen Kopien von Daten.

Call Processing Language oder. Combined Programming Language oder. Common Public License. Content Protection for Pre-Recorded Media , Kopierschutzverfahren der DVD-Audio. Common Public Radio Interface. Content Protection for Recordable Media. Common Pattern Specification Language. Central Processing Unit. Central Processing Unit Identification. Cyclic Redundancy Check , Verfahren zur Ermittlung von Übertragungsfehlern. Content Relationship Engine.

Certificate Revocation List. Common-Scrambling-Algorithmus oder. Connector, Switch, Attenuator theory. Common System Interface. Compatibility Support Module. Communicating Sequential Processes. Cascading Style Sheets oder. Content Scramble System. Character Separated Values, Comma Separated Values. Capture the Flag. Compute Unified Device Architecture. Character User Interface, d. Zeichenorientierte Benutzerschnittstelle. Capacity Upgrade on Demand. Common Unix Printing System.

Concurrent Versions System. Common Warehouse Metamodel. Disk to disk to tape Backup. Digital Audio Extraction. Data Abstraction Layer. Data Access Objects Microsoft oder.

Data Access Object Entwurfsmuster oder. Directory Access Protocol. Dümmster anzunehmender User. daily active user — Facebook: täglich aktive r Benutzer. Database management system. Data Communication Equipment oder. Distributed Computing Environment. Digital Camera Images. Data Control Language oder. DIGITAL Command Language. Dynamic Code Obfuscation. Distributed Component Object Model.

Dynamic Channel Selection. Diskrete Cosinus Transformation. Direct Coupled Transistor Logic. Double Density Diskette. Device Driver Interface. Data Definition Language. Distributed Denial of Service. Digital Data Storage oder. Direct Digital Synthesis oder. Direct Draw Surface. Direct Data Exchange. Digital Enhanced Cordless Telecommunications.

Data Execution Prevention. Data Encryption Standard. Distributed File System oder. Dynamic Frequency Selection oder. Depth-First Search. Datenfernübertragung engl. Dynamic Host Configuration Protocol. Dynamic HTML , Kombination von Hypertext Markup Language und JavaScript. Direct Internet Message Encapsulation. Dual Inline Memory Module. Distributed Interactive Simulation. Directory Information Tree. Document Lifecycle Management.

Digital Light Processing. Dynamic Language Runtime, siehe. Digital Millennium Copyright Act. Digital Micromirror Device. Desktop Management Interface oder. Direct Media Interface. Data Manipulation Language. Dokumentenmanagementsystem Document Management System. Distributed Management Task Force. Demilitarized Zone Demilitarisierte Zone. DNS-based Blackhole List. Department of Defense.

Disk Operating System oder. Data Path Array. Desktop Purchasing System oder. Data Protection System. Data Path Unit. Dell Remote Access Controller. Dynamic Random Access Memory. Direct Rendering Infrastructure. Data Retrieval Language. Digital Rights Management. Document Related Technologies. double-sided Diskette oder Speichermodul. Distributed Systems Architecture oder. Directory System Agent. Digital Subscriber Line oder.

Domain Specific Language. Digital Signal Processor. Data Set Ready. Direct Sequence Spread Spectrum. Document Style Semantics and Specification Language. Document Type Definition.

Data Terminal Equipment. Data Transfer Object. Data Terminal Ready. Directory User Agent. Digital Video Broadcasting. Digital Versatile Disc. Digital Visual Interface. Distributed Version Control System Verteilte Versionsverwaltung. Diskrete Wavelet-Transformation. Drawing Interchange Format auch Drawing Exchange Format. Enterprise Architecture. Enterprise Application Integration.

Enterprise Architecture Management. Extended Binary Coded Decimals Interchange Code. Extended Backus-Naur Form. Error-correcting code. Enterprise Content-Management. European Computer Manufacturers Association. Extended Capability Port oder. Encryption Control Protocol. Extra-high Density Diskette. Enhanced Disk Drive Services PC- BIOS Funktionen für Zugriff auf Festplatten. Electronic Device Description Language. Enhanced Data Rates for GSM Evolution. Electronic Data Interchange. Extended Display Identification Data.

Electronic Document Management. Electronic Data Processing. Elektronische Datenverarbeitung , engl. Electrically Erasable Programmable Read-Only Memory. Extensible Firmware Interface. Encrypting File System. Enhanced Graphics Adapter. Enhanced Host Controller Interface. Electronic Industries Alliance , bekannt als V. Europäischer Installationsbus. Enhanced Integrated Device Electronics. Enhanced Interior Gateway Routing Protocol. Extended Industry Standard Architecture.

Enhanced Intel SpeedStep Technology. Enterprise Java Beans. EJB Query Language. Extended Memory 64 Technology, alter Name von Intel Expanded Memory Specification. Elektromagnetische Verträglichkeit.

Enterprise Objects Framework. End Of Life. Erasable Programmable Logic Device. Enhanced Parallel Port oder. Encrypting PIN Pad oder. Enhanced Performance Profiles bei RAM. Erasable Programmable Read Only Memory. Encapsulated PostScript.

Electronic Performance Support System. Enterprise Service Bus. Enterprise Resource Planning. Enterprise Service. Extended System Configuration Data. EFI System Partition, siehe Definition in GUID Partition Table. Extended Service Set Identifier. End of Transmission Block, ein Steuerzeichen bei der Datenübertragung. End User Computing Satisfaction. Eingabe — Verarbeitung — Ausgabe EVA-Prinzip oder. Enterprise Virtual Array Disk Array von Hewlett Packard für mehrere Terabyte Daten.

Exchangeable Image File Format for Digital Still Cameras. Fully Automatic Installation. Frequently Asked Questions.

First-Come First-Served, siehe First In — First Out. Floppy Disk Drive. Fiber Distributed Data Interface. Frequency Division Multiple Access. Fast Fourier Transform schnelle Fourier-Transformation. Floating Gate Array. Frequency Hopping Spread Spectrum. First In — First Out. First In — Last Out , siehe Last In — First Out. Free Lossless Audio Codec. Floating Point Operation Gleitkommaoperation. Floating Point Operations per Second.

Field Programmable Gate Array. Field Programmable Logic Array. Frames per Second Bilder pro Sekunde. Bildfrequenz oder. First-Person Shooter. Floating Point Unit Gleitkommaeinheit , numerischer Coprozessor. Fully Qualified Domain Name. Full Scene Antialiasing. Finite State Machine. File Transfer Protocol. Fibre To The Home. Generic Array Logic. Gigabit Interface Converter. Global Catalog. GNU Compiler Collection.

Graphics Double Data Rate. Group Identification, siehe Benutzer- und Rechteverwaltung unter Unix. Graphics Interchange Format. Gateway Load Balancing Protocol. OpenGL Utility Library.

OpenGL Utility Toolkit. Geography Markup Language. Generalized Multiprotocol Label Switching Weiterentwicklung von MPLS. GNU 's Not Unix ein rekursives Akronym , siehe GNU-Projekt. Generic Object Oriented Substation Events. Guided Procedures. GNU General Public License. General Packet Radio Service. Graphics Processing Unit. Gecko Runtime Environment oder. Generic Routing Encapsulation.

Grand Unified Bootloader. Global System for Mobile Communications. Graphical User Interface. Globally Unique Identifier. Hardware Abstraction Layer. Homebanking Computer Interface. Human Computer Interaction. High-bandwidth Digital Content Protection. Hauptverband des Deutschen Einzelhandels. Hardware Description Language. High-Level Data Link Control. High Definition Multimedia Interface. High Dynamic Range Rendering. High Definition Television. Hercules Graphics Card.

Human Interface Device. Host Identity Protocol. For most companies, the cloud represents operating expense, not capital expense. You're not buying servers, you're basically paying per unit of time or unit of storage. That provides tremendous flexibility for many companies who just don't have the CapEx in their budgets to still be able to get important, innovation-driving projects done.

Another huge benefit of the cloud is the flexibility that it provides — the elasticity, the ability to dramatically raise or dramatically shrink the amount of resources that are consumed. You can only imagine if a company was in their own data centers, how hard that would have been to grow that quickly. The ability to dramatically grow or dramatically shrink your IT spend essentially is a unique feature of the cloud.

These kinds of challenging times are exactly when you want to prepare yourself to be the innovators … to reinvigorate and reinvest and drive growth forward again.

We've seen so many customers who have prepared themselves, are using AWS, and then when a challenge hits, are actually able to accelerate because they've got competitors who are not as prepared, or there's a new opportunity that they spot. We see a lot of customers actually leaning into their cloud journeys during these uncertain economic times. Do you still push multi-year contracts, and when there's times like this, do customers have the ability to renegotiate?

Many are rapidly accelerating their journey to the cloud. Some customers are doing some belt-tightening. What we see a lot of is folks just being really focused on optimizing their resources, making sure that they're shutting down resources which they're not consuming. You do see some discretionary projects which are being not canceled, but pushed out.

Every customer is free to make that choice. But of course, many of our larger customers want to make longer-term commitments, want to have a deeper relationship with us, want the economics that come with that commitment. We're signing more long-term commitments than ever these days. We provide incredible value for our customers, which is what they care about.

That kind of analysis would not be feasible, you wouldn't even be able to do that for most companies, on their own premises. So some of these workloads just become better, become very powerful cost-savings mechanisms, really only possible with advanced analytics that you can run in the cloud.

In other cases, just the fact that we have things like our Graviton processors and … run such large capabilities across multiple customers, our use of resources is so much more efficient than others. We are of significant enough scale that we, of course, have good purchasing economics of things like bandwidth and energy and so forth.

So, in general, there's significant cost savings by running on AWS, and that's what our customers are focused on. The margins of our business are going to … fluctuate up and down quarter to quarter. It will depend on what capital projects we've spent on that quarter. Obviously, energy prices are high at the moment, and so there are some quarters that are puts, other quarters there are takes.

The important thing for our customers is the value we provide them compared to what they're used to. And those benefits have been dramatic for years, as evidenced by the customers' adoption of AWS and the fact that we're still growing at the rate we are given the size business that we are. That adoption speaks louder than any other voice. Do you anticipate a higher percentage of customer workloads moving back on premises than you maybe would have three years ago? Absolutely not.

We're a big enough business, if you asked me have you ever seen X, I could probably find one of anything, but the absolute dominant trend is customers dramatically accelerating their move to the cloud. Moving internal enterprise IT workloads like SAP to the cloud, that's a big trend.

Creating new analytics capabilities that many times didn't even exist before and running those in the cloud. More startups than ever are building innovative new businesses in AWS. Our public-sector business continues to grow, serving both federal as well as state and local and educational institutions around the world.

It really is still day one. The opportunity is still very much in front of us, very much in front of our customers, and they continue to see that opportunity and to move rapidly to the cloud. In general, when we look across our worldwide customer base, we see time after time that the most innovation and the most efficient cost structure happens when customers choose one provider, when they're running predominantly on AWS.

A lot of benefits of scale for our customers, including the expertise that they develop on learning one stack and really getting expert, rather than dividing up their expertise and having to go back to basics on the next parallel stack.

That being said, many customers are in a hybrid state, where they run IT in different environments. In some cases, that's by choice; in other cases, it's due to acquisitions, like buying companies and inherited technology. We understand and embrace the fact that it's a messy world in IT, and that many of our customers for years are going to have some of their resources on premises, some on AWS.

Some may have resources that run in other clouds. We want to make that entire hybrid environment as easy and as powerful for customers as possible, so we've actually invested and continue to invest very heavily in these hybrid capabilities.

A lot of customers are using containerized workloads now, and one of the big container technologies is Kubernetes. We have a managed Kubernetes service, Elastic Kubernetes Service, and we have a … distribution of Kubernetes Amazon EKS Distro that customers can take and run on their own premises and even use to boot up resources in another public cloud and have all that be done in a consistent fashion and be able to observe and manage across all those environments.

So we're very committed to providing hybrid capabilities, including running on premises, including running in other clouds, and making the world as easy and as cost-efficient as possible for customers. Can you talk about why you brought Dilip Kumar, who was Amazon's vice president of physical retail and tech, into AWS as vice president applications and how that will play out?

He's a longtime, tenured Amazonian with many, many different roles — important roles — in the company over a many-year period. Dilip has come over to AWS to report directly to me, running an applications group. We do have more and more customers who want to interact with the cloud at a higher level — higher up the stack or more on the application layer.

We talked about Connect, our contact center solution, and we've also built services specifically for the healthcare industry like a data lake for healthcare records called Amazon HealthLake. We've built a lot of industrial services like IoT services for industrial settings, for example, to monitor industrial equipment to understand when it needs preventive maintenance. We have a lot of capabilities we're building that are either for … horizontal use cases like Amazon Connect or industry verticals like automotive, healthcare, financial services.

We see more and more demand for those, and Dilip has come in to really coalesce a lot of teams' capabilities, who will be focusing on those areas. You can expect to see us invest significantly in those areas and to come out with some really exciting innovations.

Would that include going into CRM or ERP or other higher-level, run-your-business applications? I don't think we have immediate plans in those particular areas, but as we've always said, we're going to be completely guided by our customers, and we'll go where our customers tell us it's most important to go next. It's always been our north star. Correction: This story was updated Nov. Bennett Richardson bennettrich is the president of Protocol.

Prior to joining Protocol in , Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company.

Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University. Prior to joining Protocol in , he worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter.

He has previously worked at MIT Technology Review, Gizmodo, and New Scientist, and has held lectureships at the University of Oxford and Imperial College London. He also holds a doctorate in engineering from the University of Oxford. We launched Protocol in February to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication. As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent.

Source Code will be published and sent for the next few weeks, but it will also close down in December. Building this publication has not been easy; as with any small startup organization, it has often been chaotic. But it has also been hugely fulfilling for those involved. We could not be prouder of, or more grateful to, the team we have assembled here over the last three years to build the publication. They are an inspirational group of people who have gone above and beyond, week after week.

Today, we thank them deeply for all the work they have done. We also thank you, our readers, for subscribing to our newsletters and reading our stories. We hope you have enjoyed our work. As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia. org and is the author of "Campaign ' A Turning Point for Digital Media," a book about how the presidential campaigns used digital media and data.

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. And he said that while some MLops systems can manage a larger number of models, they might not have desired features such as robust data visualization capabilities or the ability to work on premises rather than in cloud environments.

As companies expand their use of AI beyond running just a few ML models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, many machine learning practitioners Protocol interviewed for this story say that they have yet to find what they need from prepackaged MLops systems. Companies hawking MLops platforms for building and managing machine learning models include tech giants like Amazon, Google, Microsoft, and IBM and lesser-known vendors such as Comet, Cloudera, DataRobot, and Domino Data Lab.

It's actually a complex problem. Intuit also has constructed its own systems for building and monitoring the immense number of ML models it has in production, including models that are customized for each of its QuickBooks software customers. The model must recognize those distinctions. For instance, Hollman said the company built an ML feature management platform from the ground up.

For companies that have been forced to go DIY, building these platforms themselves does not always require forging parts from raw materials. DBS has incorporated open-source tools for coding and application security purposes such as Nexus, Jenkins, Bitbucket, and Confluence to ensure the smooth integration and delivery of ML models, Gupta said.

Intuit has also used open-source tools or components sold by vendors to improve existing in-house systems or solve a particular problem, Hollman said. However, he emphasized the need to be selective about which route to take. I think that the best AI will be a build plus buy. However, creating consistency through the ML lifecycle from model training to deployment to monitoring becomes increasingly difficult as companies cobble together open-source or vendor-built machine learning components, said John Thomas, vice president and distinguished engineer at IBM.

The reality is most people are not there, so you have a whole bunch of different tools. Companies struggling to find suitable off-the-shelf MLops platforms are up against another major challenge, too: finding engineering talent. Many companies do not have software engineers on staff with the level of expertise necessary to architect systems that can handle large numbers of models or accommodate millions of split-second decision requests, said Abhishek Gupta, founder and principal researcher at Montreal AI Ethics Institute and senior responsible AI leader and expert at Boston Consulting Group.

For one thing, smaller companies are competing for talent against big tech firms that offer higher salaries and better resources. For companies with less-advanced AI operations, shopping at the existing MLops platform marketplace may be good enough, Hollman said.

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Please check back soon for future events, and sign up to receive invitations to our events and briefings. December 1, Speaker Series on California's Future — Virtual Event. November 30, Virtual Event. November 18, Annual Water Conference — In-Person and Online.

We believe in the power of good information to build a brighter future for California. Help support our mission. Mark Baldassare , Dean Bonner , Rachel Lawler , and Deja Thomas. Supported with funding from the Arjay and Frances F. Miller Foundation and the James Irvine Foundation. California voters have now received their mail ballots, and the November 8 general election has entered its final stage.

Amid rising prices and economic uncertainty—as well as deep partisan divisions over social and political issues—Californians are processing a great deal of information to help them choose state constitutional officers and state legislators and to make policy decisions about state propositions.

The midterm election also features a closely divided Congress, with the likelihood that a few races in California may determine which party controls the US House. These are among the key findings of a statewide survey on state and national issues conducted from October 14 to 23 by the Public Policy Institute of California:. Today, there is a wide partisan divide: seven in ten Democrats are optimistic about the direction of the state, while 91 percent of Republicans and 59 percent of independents are pessimistic.

Californians are much more pessimistic about the direction of the country than they are about the direction of the state. Majorities across all demographic groups and partisan groups, as well as across regions, are pessimistic about the direction of the United States. A wide partisan divide exists: most Democrats and independents say their financial situation is about the same as a year ago, while solid majorities of Republicans say they are worse off.

Regionally, about half in the San Francisco Bay Area and Los Angeles say they are about the same, while half in the Central Valley say they are worse off; residents elsewhere are divided between being worse off and the same. The shares saying they are worse off decline as educational attainment increases. Strong majorities across partisan groups feel negatively, but Republicans and independents are much more likely than Democrats to say the economy is in poor shape.

Today, majorities across partisan, demographic, and regional groups say they are following news about the gubernatorial election either very or fairly closely. In the upcoming November 8 election, there will be seven state propositions for voters. Due to time constraints, our survey only asked about three ballot measures: Propositions 26, 27, and For each, we read the proposition number, ballot, and ballot label.

Two of the state ballot measures were also included in the September survey Propositions 27 and 30 , while Proposition 26 was not. This measure would allow in-person sports betting at racetracks and tribal casinos, requiring that racetracks and casinos offering sports betting make certain payments to the state to support state regulatory costs.

It also allows roulette and dice games at tribal casinos and adds a new way to enforce certain state gambling laws. Fewer than half of likely voters say the outcome of each of these state propositions is very important to them.

Today, 21 percent of likely voters say the outcome of Prop 26 is very important, 31 percent say the outcome of Prop 27 is very important, and 42 percent say the outcome of Prop 30 is very important. Today, when it comes to the importance of the outcome of Prop 26, one in four or fewer across partisan groups say it is very important to them.

About one in three across partisan groups say the outcome of Prop 27 is very important to them. Fewer than half across partisan groups say the outcome of Prop 30 is very important to them. When asked how they would vote if the election for the US House of Representatives were held today, 56 percent of likely voters say they would vote for or lean toward the Democratic candidate, while 39 percent would vote for or lean toward the Republican candidate. Democratic candidates are preferred by a point margin in Democratic-held districts, while Republican candidates are preferred by a point margin in Republican-held districts.

Abortion is another prominent issue in this election. When asked about the importance of abortion rights, 61 percent of likely voters say the issue is very important in determining their vote for Congress and another 20 percent say it is somewhat important; just 17 percent say it is not too or not at all important. With the controlling party in Congress hanging in the balance, 51 percent of likely voters say they are extremely or very enthusiastic about voting for Congress this year; another 29 percent are somewhat enthusiastic while 19 percent are either not too or not at all enthusiastic.

Today, Democrats and Republicans have about equal levels of enthusiasm, while independents are much less likely to be extremely or very enthusiastic. As Californians prepare to vote in the upcoming midterm election, fewer than half of adults and likely voters are satisfied with the way democracy is working in the United States—and few are very satisfied.

Satisfaction was higher in our February survey when 53 percent of adults and 48 percent of likely voters were satisfied with democracy in America. Today, half of Democrats and about four in ten independents are satisfied, compared to about one in five Republicans. Notably, four in ten Republicans are not at all satisfied. In addition to the lack of satisfaction with the way democracy is working, Californians are divided about whether Americans of different political positions can still come together and work out their differences.

Forty-nine percent are optimistic, while 46 percent are pessimistic. Today, in a rare moment of bipartisan agreement, about four in ten Democrats, Republicans, and independents are optimistic that Americans of different political views will be able to come together. Notably, in , half or more across parties, regions, and demographic groups were optimistic. Today, about eight in ten Democrats—compared to about half of independents and about one in ten Republicans—approve of Governor Newsom.

Across demographic groups, about half or more approve of how Governor Newsom is handling his job. Approval of Congress among adults has been below 40 percent for all of after seeing a brief run above 40 percent for all of Democrats are far more likely than Republicans to approve of Congress. Fewer than half across regions and demographic groups approve of Congress. Approval in March was at 44 percent for adults and 39 percent for likely voters.

Across demographic groups, about half or more approve among women, younger adults, African Americans, Asian Americans, and Latinos. Views are similar across education and income groups, with just fewer than half approving. Approval in March was at 41 percent for adults and 36 percent for likely voters. Across regions, approval reaches a majority only in the San Francisco Bay Area.

Across demographic groups, approval reaches a majority only among African Americans. This map highlights the five geographic regions for which we present results; these regions account for approximately 90 percent of the state population.

Residents of other geographic areas in gray are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately.

The PPIC Statewide Survey is directed by Mark Baldassare, president and CEO and survey director at the Public Policy Institute of California. Coauthors of this report include survey analyst Deja Thomas, who was the project manager for this survey; associate survey director and research fellow Dean Bonner; and survey analyst Rachel Lawler. The Californians and Their Government survey is supported with funding from the Arjay and Frances F.

Findings in this report are based on a survey of 1, California adult residents, including 1, interviewed on cell phones and interviewed on landline telephones. The sample included respondents reached by calling back respondents who had previously completed an interview in PPIC Statewide Surveys in the last six months.

Interviews took an average of 19 minutes to complete. Interviewing took place on weekend days and weekday nights from October 14—23, Cell phone interviews were conducted using a computer-generated random sample of cell phone numbers. Additionally, we utilized a registration-based sample RBS of cell phone numbers for adults who are registered to vote in California.

All cell phone numbers with California area codes were eligible for selection. After a cell phone user was reached, the interviewer verified that this person was age 18 or older, a resident of California, and in a safe place to continue the survey e.

Cell phone respondents were offered a small reimbursement to help defray the cost of the call. Cell phone interviews were conducted with adults who have cell phone service only and with those who have both cell phone and landline service in the household. Landline interviews were conducted using a computer-generated random sample of telephone numbers that ensured that both listed and unlisted numbers were called.

Additionally, we utilized a registration-based sample RBS of landline phone numbers for adults who are registered to vote in California. All landline telephone exchanges in California were eligible for selection. For both cell phones and landlines, telephone numbers were called as many as eight times. When no contact with an individual was made, calls to a number were limited to six. Also, to increase our ability to interview Asian American adults, we made up to three additional calls to phone numbers estimated by Survey Sampling International as likely to be associated with Asian American individuals.

Accent on Languages, Inc. The survey sample was closely comparable to the ACS figures. To estimate landline and cell phone service in California, Abt Associates used state-level estimates released by the National Center for Health Statistics—which used data from the National Health Interview Survey NHIS and the ACS.

The estimates for California were then compared against landline and cell phone service reported in this survey. We also used voter registration data from the California Secretary of State to compare the party registration of registered voters in our sample to party registration statewide. The sampling error, taking design effects from weighting into consideration, is ±3.

This means that 95 times out of , the results will be within 3. The sampling error for unweighted subgroups is larger: for the 1, registered voters, the sampling error is ±4. For the sampling errors of additional subgroups, please see the table at the end of this section.

Sampling error is only one type of error to which surveys are subject. Results may also be affected by factors such as question wording, question order, and survey timing. We present results for five geographic regions, accounting for approximately 90 percent of the state population.

Residents of other geographic areas are included in the results reported for all adults, registered voters, and likely voters, but sample sizes for these less-populous areas are not large enough to report separately. We also present results for congressional districts currently held by Democrats or Republicans, based on residential zip code and party of the local US House member.

We compare the opinions of those who report they are registered Democrats, registered Republicans, and no party preference or decline-to-state or independent voters; the results for those who say they are registered to vote in other parties are not large enough for separate analysis.

We also analyze the responses of likely voters—so designated per their responses to survey questions about voter registration, previous election participation, intentions to vote this year, attention to election news, and current interest in politics.

The percentages presented in the report tables and in the questionnaire may not add to due to rounding. Additional details about our methodology can be found at www. pdf and are available upon request through surveys ppic.

October 14—23, 1, California adult residents; 1, California likely voters English, Spanish. Margin of error ±3.

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Special Reports. Power And Timing Modelling, Optimization and Simulation, ace binary option indicator. Java Network Launching Protocol. Web Distributed Data Exchange. Prior to joining Protocol inhe worked on the business desk at The New York Times, where he edited the DealBook newsletter and wrote Bits, the weekly tech newsletter. Prior to joining PPIC, she was a research assistant with the social and demographic trends team at the Pew Research Center. Logical Data Unit.