With help-wanted signs dotting the landscape and recruiting websites looking for both floor-level jobs and advanced engineers, some businesses are venturing outside their human resource departments for help.

Employment opportunities in Wichita aerospace market abound

Allegis Group firm Actalent on Thursday announced a three-year partnership with Central Manufacturing Technology Institute (CMTI) to boost organisations' R&D efforts in the manufacturing technology sector. The alliance will draw on each organization's ...

Actalent announces 3-yr partnership with Central Manufacturing Technology Institute

The alliance will draw on each organization's resources and expertise to accelerate the transition to smart manufacturing, providing a streamlined more efficient, and cost-effective transition for global clients,

Mumbai, Aug 31 (PTI) Allegis Group firm Actalent on Thursday announced a three-year partnership with Central Manufacturing Technology Institute (CMTI) to boost organisations' R&D efforts in the manufacturing technology sector. The alliance will draw on ...

HANOVER, Md., Aug. 30, 2023 /PRNewswire/ -- Actalent, a leading engineering and sciences services and talent solutions company, today announced a three-year partnership with India -based Central Manufacturing Technology Institute (CMTI) to boost both organizations' research and development (R&D) efforts in the manufacturing technology sector.

Actalent Partners with India's Central Manufacturing Technology Institute (CMTI) to Offer Enhanced Manufacturing Services to Global Clients

Actalent, a leading engineering and sciences services and talent solutions company, today announced a three-year partnership with India-based Central Manufacturing Technology Institute (CMTI) to boost both organizations' research and development (R&D) efforts in the manufacturing technology sector.

PRNewswire Hanover [Germany] August 30 Actalent a leading engineering and sciences services and talent solutions company today announced a three-year partnership with India-based Central Manufacturing

Actalent

actalent

What makes some leaders produce excellent work while others barely do a part of their job? Leaders are entrusted with great responsibility. How they behave and act has a large impact on the organization and its people. Competence, knowledge and skills are important to become a leader, but how those things are put to use matters as much. When leaders aren’t conscious of their time, let fear guide their decisions, worry about being disliked, and use excuses to delay or put off things that need their time and attention, they fail to do their job. Their behaviors push the organization back instead of lifting it up. Effective leaders, though rare, are inspirational. They bring people together and enable them to collectively achieve great things together. They put the welfare of the organization and their people above their own self interests. Here are the 9 behaviors I have observed in my career that sets effective leaders apart: They aren’t afraid to challenge the status quo Leaders who play safe do things the way they have always been done. Afraid to challenge, insecure to take risks and lack of confidence prevents them from exploring anything that’s outside their comfort zone. They shut down innovative ideas, better ways to solve problems and even new practices that can be a game changer for their organization and their team. Copy pasting past knowledge without questioning it or showing resistance towards new ideas and beliefs keeps them locked in a cycle of ineffectiveness and inefficiency. Effective leaders are risk takers. They defy conventional wisdom and challenge outdated beliefs and practices. They aren’t afraid to disagree, assert their opinion or make bold decisions that are necessary for growth and progress. Thinking ahead makes them think differently. They’re able to adapt to the future. The true mark of a leader is the willingness to stick with a bold course of action — an unconventional business strategy, a unique product-development roadmap, a controversial marketing campaign — even as the rest of the world wonders why you're not marching in step with the status quo. In other words, real leaders are happy to zig while others zag. They understand that in an era of hyper-competition and non-stop disruption, the only way to stand out from the crowd is to stand for something special. — Bill Taylor Effective leaders don’t try to fit in, they stand out. They are willing to make unpopular decisions Leaders make 100s of decisions throughout the day—some significant and others inconsequential. Leaders who focus on earning likes and being nice go with popular decisions even though such decisions may not be impactful or give them the desired results. Nodding yes to others even when they disagree or keeping quiet with the fear of being disliked leads to poor choices and bad decisions. These leaders also don’t pay attention to their biases: They stick with their opinion and reject all contradicting evidence. Within certain social contexts, choose what’s easy over what’s right. Optimize for short term pain at the cost of long term gain. Keep investing in sunk costs and refuse to rethink their bad decision to protect their ego. Truthseeking, the desire to know the truth regardless of whether the truth aligns with the beliefs we currently hold, is not naturally supported by the way we process information. We might think of ourselves as open-minded and capable of updating our beliefs based on new information, but the research conclusively shows otherwise. Instead of altering our beliefs to fit new information, we do the opposite, altering our interpretation of that information to fit our beliefs. — Annie Duke Effective leaders don’t like to be part of a popularity contest. They know that it’s their job to make hard decisions even if those decisions make them unpopular or get them some stares in the short term. They are also very tactful—they know which decisions to let go and let others have their way and when they need to put their foot down and refuse to compromise. They make better decisions by: Encouraging disagreements and conflicting opinions and paying attention to them. Being highly aware of their biases. Not tying decisions to outcomes. Not copy pasting past success. Factoring both data and intuition into the process. Effective leaders don’t optimize for popularity, they optimize for making better decisions. They don’t let urgency eat up into their priorities Leaders who are always involved in solving urgent issues—putting out fires, handling a customer complaint, delayed delivery etc—react to what comes their way instead of consciously spending time on things that are crucial for an organization's growth in the long term. Reacting to urgent tasks while pushing important work aside makes them solve short term problems at the cost of more future oriented, forward looking activities. More and more urgent issues keep cropping up which wastes everyone’s time and energy. Effective leaders are very conscious of how and where they spend their time. They’re highly proactive about strategic thinking, planning and reducing time wasting urgent activities. Aligning their time and energy with the future goals of the organization reduces urgent issues, pushes the organization forward and makes employees feel happy and motivated. They use the Eisenhower matrix to plan and prioritize important work on their calendar and ensure it gets done. In doing this, delegation is a big part of their strategy. It not only frees up their time to be effective in their role, it also gives great opportunities to their team to step up and take bigger and better responsibilities. An effective leader must step back, look at the big picture, and make sure the important things are not being pushed out of the way by the seemingly urgent needs of the moment. — Ken Blanchard Effective leaders plan their time well, not take it for granted. They don’t attend meetings that aren’t worth their time Leaders whose calendars are packed with back to back meetings are bound to be busy. Packed calendars make them feel important. They feel valued. They justify their busyness by saying “I am so busy. I have important things to say and do. I must be adding value.” A Leader's role may demand them to attend a lot of meetings, but not all meetings are worth their time. Busyness creates an illusion of productivity. They spend a lot of time working without creating value. It also saves them from the discomfort from doing hard things—things that will move them forward but require them to step outside their comfort zone. Being busy with meetings is then the perfect excuse to avoid doing the work they fear or find particularly difficult to do. Effective leaders don’t attend a meeting just because others invite them to it and they don’t schedule a meeting for things that can be discussed and solved over an email, chat, or a phone call. Less meetings are not only less taxing on their schedule, they give them the mental space needed to do quality work. They apply the 80-20 rule to meetings—only 20% of your meetings account for 80% of your results. Richard Koch explains the 80/20 principle this way — The 80/20 Principle asserts that a minority of causes, inputs or effort usually lead to a majority of the results, outputs or rewards. Taken literally, this means that, for example, 80 percent of what you achieve in your job comes from 20 percent of the time spent. Thus for all practical purposes, four-fifths of the effort – a dominant part of it – is largely irrelevant. This is contrary to what people normally expect. Effective leaders optimize their meeting time using these steps: Delegate: Identify which meetings are worth attending. Are these meetings only you can do? Which meetings can you delegate? Who else can take your place? Declutter: Which meetings are not even required? Strike them off. Reduce: Which of your meetings go beyond 30 mins? Why do they need so much time? Do you have weekly or biweekly meetings whose frequency can be reduced? Attend: Highlight the ones that are absolutely important and only you can attend. Effective leaders make better decisions with less meetings, not more. They do the right thing instead of trying to be right Leaders who want to be right try to prove their smartness. They show off their brilliance by being the person with all the answers. Thinking it’s their job as a leader to know everything makes them too afraid to admit ignorance. They never say “I don’t know” because saying it might expose them to others who will consider them unsuitable and unworthy of their position. Failing to admit they’re wrong or they don’t know something leads to poor choices and terrible decisions. Effective leaders don’t think this way. They know they aren’t perfect or have superhuman qualities. Much like everyone else, they too are learning and growing and don’t have answers to all the problems at work. They don’t let their lack of knowledge or a gap in their understanding get in the way of making the right decision. They may not know the answers themselves, but they have the great ability to find those answers. They do the right thing by: Acknowledging when they are wrong or when they don’t know something. Seeking diverse opinions and evaluating different options. Choosing the best option irrespective of who suggested it. Effective leaders consider vulnerability as a strength, not weakness. Vulnerability sounds like truth and feels like courage. Truth and courage aren't always comfortable, but they're never weakness. — Brené Brown They address the root cause instead of solving superficial problems Leaders who rush to solve issues don’t pay attention to the real problem. Desire to solve the problem quickly makes them see what’s right in front of them while ignoring the real issue that caused it. Addressing the symptom in the short term without considering the root cause may be instantly gratifying, but delaying it is more harmful in the long term. Ignoring the root cause only makes it worse. As the problem repeats many times over, it not only wastes everyone’s time and effort, but also leads to frustration and anxiety. Effective leaders don’t turn a blind eye to real problems. Even if they have to make some short term fixes to put out fires, they never lose sight of the real issue that deserves their time and attention. They use the five-whys technique to go from superficial understanding of the problem to its underlying root cause. This is the way it works—ask why the issue occurred and use the answer as the premise for the next question repeating this whole process five times to dig deeper into the actual root cause. By repeating “why” five times, the nature of the problem and its solution becomes clear. Here’s an example: Q: “Why did you take longer than expected to deliver on the project?” A: I had to rework on some of the features. Q: “Why did you need to rework on some features?” A: I made wrong assumptions about certain requirements. Q: “Why did you make wrong assumptions about these requirements?” A: I did not clarify the requirements at the beginning. Q: “Why did you not clarify the requirements in the beginning?” A: I waited too long to start work and then assumed it was too late to ask any clarifying questions. Q: “Why did you wait too long to start work?” A: I was overconfident in my abilities. Effective leaders don’t stop at the first level of the problem, they like to dig deeper. They don’t let hierarchy get in the way of building meaningful connections Leaders who distance themselves from their people lose sight of the real issues that plague their team’s productivity and performance. Every step up the ladder adds to the gap. Leading with assumptions on what their team needs or the problems they face hurts their organization—employees feel unheard and unsupportive when their leader fails to address their concerns. Their biggest excuse? Lack of time. Keeping themselves busy with other work priorities while not making time for their team is a costly mistake. Effective leaders prioritize their people above everything else. They know that without diving deep into people’s minds, they can never develop the intelligence and perspective required to stay close to reality—going directly to the source and hearing it from their own mouth without any presumptions is the only way. For them, connecting with their employees isn’t a one-off thing. It’s a big part of their strategy and agenda. They consciously prioritize and make time for doing 1-1 meetings—not just with their direct reports but also those who indirectly report to them. One-on-ones provide an excellent mechanism for information and ideas to flow up the organization and should be part of your design. — Ben Horowitz Effective leaders make one-on-ones a part of their strategy to keep in touch with real problems. They don’t avoid discussions that require their time and attention Leaders who consider conflict bad avoid it by pretending it does not exist. Avoiding conflict, not taking responsibility, denying or worse delaying it doesn’t help. Not paying attention to the conflict does not make it disappear, it only makes it worse. Not getting a closure keeps people’s minds preoccupied with the conflict instead of putting that time and energy to get work done. Unresolved emotions create a mental imbalance that harms their productivity and performance. Effective leaders embrace conflict and the discomfort that comes with it. They don’t treat conflicts “bad” or a thing to avoid, but rather as the reality of every workplace that provides tremendous opportunities to improve and do better. Crucial conversations well held accelerate the building of trust, they not only not damage it, they create a sense of connection — Kerry Patterson They use the following practices to navigate conflict: They start with defining their motive—what they wish to achieve from the conversation—without generalizing or exaggerating it. They approach the discussion with an element of trust and not the intention to blame or attack. They share observations without passing any judgments and talk about the impact to communicate their message effectively. They use questions to help others arrive at their own solutions instead of telling them what to do. Instead of staying with their narrative, they are willing to change their views. Effective leaders treat conflicts as a sign of a healthy workplace and not something to avoid. They embrace uncertainty and unknowns Leaders who like certainty find it hard to tackle unknowns. They get stuck in analysis paralysis and try to delay decisions that involve uncertainty and unknowns. Trying to be 100% certain in their decision makes them lose valuable opportunities. They become reluctant to take risks and make safe bets even though such decisions do not lead to growth. Effective leaders purposefully cut through ambiguity as they see opportunity in uncertainty. They navigate change by stepping up and embracing unpredictability. Not waiting for complete information to make a decision helps them put their ideas out there, seek feedback and iterate on it. They deal with ambiguity using these 7 practices: They zoom out and zoom in to combine future opportunities with present challenges. They separate knowns from unknowns to identify relevant and missing information. They build cross-disciplinary thinking for creative problem solving. Instead of only relying on data to make decisions, they make ambiguous decisions by factoring in their intuition. Willingness to step outside their comfort zone makes them embrace risks and uncertainty with courage and action. Instead of sticking with a wrong decision, they don’t hesitate to change direction. They take responsibility which enables them to feel in control and take constructive action. Remember most of the future is unforeseeable. Learn to coexist with chaos. Factor it into your plans. Accept that failure is always a possibility, even if you are one of the good guys; those who believe failure is not an option never plan for it. Some things are predictable and manageable, but the farther away in time an event occurs, the less power you have over it — David McRaney Effective leaders don’t find ambiguity demotivating. They see it as exhilarating, rewarding, and mentally stimulating. Summary Leaders don’t become effective by simply acquiring knowledge and skills. Their behaviors and actions and how those skills are put to use matters as much. Effective leaders don’t rely on conventional wisdom to determine how things must be done. They challenge the status quo, encourage new ideas and creative ways to solve problems. Effective leaders make tough decisions that may not make them popular but definitely lead to growth. Effective leaders understand that pushing important work aside and reacting to urgent matters will keep them busy without being effective. They consciously plan and prioritize future oriented forward looking activities. Effective leaders don’t attend all the meetings that show up on their calendar or schedule meetings for issues that can be solved over phone, email or chat. Spending less time in meetings leaves more time to do work that matters. Effective leaders prioritize finding the right answers above the need to appear smart or show off their brilliance. They aren’t afraid to admit when they don’t know something or when they might be wrong. Effective leaders pay attention to the real issue that’s hidden from plain sight because it requires digging deeper. They use the five-whys technique to uncover the underlying root cause. Effective leaders don’t let hierarchy get in the way of connecting with people in their organization. By taking the time to understand and address their concerns, they increase their team’s productivity and performance. Effective leaders treat conflicts as a sign of a healthy workplace and not something to avoid. Even if it makes them uncomfortable, they don’t delay the discussion as delaying it only makes it worse. Effective leaders don’t let uncertainty and unknowns become a bottleneck to growth. Instead of being stuck in analysis paralysis, they make the best possible decision, put it into action and iterate on it. This story was previously published . Follow me on or here for more stories. here LinkedIn

The 9 Powerful Behaviors of Highly Effective Leaders That Sets Them Apart 

অত্যন্ত কার্যকরী নেতাদের 9টি শক্তিশালী আচরণ যা তাদের আলাদা করে

Die 9 kraftvollen Verhaltensweisen hochwirksamer Führungskräfte, die sie auszeichnen

Los 9 comportamientos poderosos de los líderes altamente efectivos que los distinguen

Les 9 comportements puissants des leaders très efficaces qui les distinguent

अत्यधिक प्रभावी नेताओं के 9 शक्तिशाली व्यवहार जो उन्हें अलग करते हैं

優れたリーダーを際立たせる、非常に有能なリーダーの 9 つの強力な行動

매우 효과적인 리더를 차별화하는 9가지 강력한 행동

Os 9 comportamentos poderosos de líderes altamente eficazes que os diferenciam

9 сильных качеств высокоэффективных лидеров, которые отличают их от других

Yüksek Etkili Liderleri Farklı Kılan 9 Güçlü Davranış

9 hành vi mạnh mẽ của các nhà lãnh đạo hiệu quả khiến họ trở nên khác biệt

高效能领导者的 9 种让他们脱颖而出的强大行为

Cassandra is a distributed, decentralized, scalable, and highly available wide-column database. In terms of CAP theorem, Cassandra stands for AP (availability and partition tolerance). It means that Cassandra prefers that all clients can find data even in cases where not all nodes are available and will work as expected when partial network failure occurs. However, it also means that the consistency of the data can be compromised in favor of availability and partition tolerance - users will see the data, but it may be stale for a while. Cassandra is designed for achieving high throughput and faster write operations. And it is precisely sacrificing consistency that allows Cassandra to be highly available. By default, Cassandra is designed to be eventually consistent, meaning that it may not provide strong consistency. This makes Cassandra suitable for applications where consistency is not a critical requirement. However, it is possible to configure Cassandra to provide strong consistency, although this can impact performance. Cassandra, being a NoSQL database, does not support table joins, foreign keys, or the ability to add columns other than the primary key in the WHERE clause while querying. These limitations should be taken into consideration before choosing to use Cassandra. Cassandra Building blocks : A column represents a key-value pair and serves as the fundamental unit of data structure. Column : acts as a container for columns that are referenced by the primary key. Row : serves as a container for tables that span across one or more Cassandra nodes. Keyspace : a container of keyspaces within Cassandra. Cluster : refers to a computer system that runs an instance of Cassandra. A node can be a physical host, a machine instance in the cloud, or even a Docker container. Node How Cassandra stores data Cassandra stores the data as a column family. It serves as a container for columns that are referenced by a primary key. A row of a column family includes several columns with key and value, and the row key serves as the primary key: A column family can store a different set of columns for each row key: Cassandra does not store columns with null values, which helps save significant storage space What is the primary key in Cassandra? The uniquely identifies each row of a table. In Cassandra, the primary key has two parts: Primary key In Cassandra, the partition key determines which node stores the data, while the clustering key determines how the data is stored within a node. For instance, consider a table with a . This primary key consists of two parts, represented by the two columns: PRIMARY KEY (city_id, event_id) 1. serves as the partition key, meaning that data will be partitioned based on the field, resulting in all rows with the same being stored on the same node. city_id city_id city_id 2. acts as the clustering key. Within each node, the data is organized and stored in sorted order based on the column. event_id event_id Clustering keys determine the storage arrangement of data within a node. It is possible to have multiple clustering keys, and any columns listed after the partition key are referred to as clustering columns. Clustering columns define the order in which data is organized on a node. Every row with partition key = "Paris" will be stored on the same node, ordered by the value of the event_id column. Data partitioning out of the box Cassandra provides data partitioning based on to reduce latency in read/write operations and increase the throughput of the system when the amount of data stored in the database becomes large. Consistent Hashing The in Cassandra is responsible for deciding how data is distributed across the Consistent Hash ring. When data is inserted into a Cassandra cluster, the partitioner applies a hashing algorithm to the . The result of this hashing algorithm determines the range in which the data falls and determines the node on which the data will be stored. partitioner partition key Coordinator node In Cassandra, each node is aware of the token assignments of other nodes through , allowing any node to handle requests for any other node's range. Therefore, a client can connect to any node to initiate read or write queries. gossip protocol The node that receives the request is known as the and can be any node in the cluster. If a key does not belong to the coordinator's range, the request is forwarded to the replicas responsible for that range. coordinator Replication Cassandra replicates data across multiple nodes to ensure high availability. Each node in Cassandra serves as a replica for a specific data range. By spreading multiple copies of the data across different replicas, Cassandra enables other replicas to handle queries for that data range in case one node is unavailable. Two settings will affect the replication process: The replication factor determines how many nodes will store copies of the same data. In a cluster with a replication factor of 3, each row will be stored on three different nodes. Each keyspace in Cassandra can have a different replication factor. In Cassandra, the first replica is assigned to the node that owns the range based on the hash of the partition key. The remaining replicas are then placed on consecutive nodes in a clockwise manner. Cassandra uses two replication strategies to determine which nodes will be responsible for the replicas: Simple replication strategy In this strategy, the first replica is placed on a node determined by the partitioner, and the succeeding replicas are placed on the subsequent nodes in a clockwise manner. This replication strategy is applicable only for a single data center cluster. Network topology strategy To ensure resilience against complete loss of data, additional replicas within the same data center are placed by moving clockwise along the ring until reaching the first node in a different data center. This arrangement helps mitigate the impact of simultaneous failures that typically occur within the same data center due to power, cooling, or network issues. When it comes to multi-datacenter configurations, you should consider the network topology strategy. This approach allows for the specification of varying replication factors for each data center, enabling control over the number of replicas to be placed in each specific location. When to use Cassandra Cassandra excels in applications that require handling large volumes of data and prioritize data availability over consistency. : It is well-suited for 1. : Cassandra is an ideal choice for IoT environments, as it can handle massive amounts of data generated by devices and sensors. Its distributed architecture enables management of geographically dispersed, large-scale data. Internet of Things (IoT) Applications 2. : Applications dealing with time-series data, such as metrics, monitoring systems, and telemetry data, benefit from Cassandra's efficient write operations and horizontal scalability. These capabilities are crucial for storing and managing extensive volumes of time-stamped data. Time-Series Data 3. : Cassandra offers high throughput and low-latency data access, making it suitable for web and mobile platforms with large user bases generating significant amounts of data. This includes social media platforms, gaming apps, and e-commerce sites. Web and Mobile Applications 4. : Cassandra supports real-time processing of big data, making it a valuable choice for applications requiring immediate insights from large datasets. Examples include recommendation engines and fraud detection systems. Real-Time Big Data Analytics 5. : Enterprises with large, distributed datasets can leverage Cassandra as a data warehouse solution. Its ability to replicate data across multiple data centers ensures high availability and disaster recovery. Distributed Data Warehouses 6. : Cassandra's high write and read throughput makes it well-suited for messaging systems that handle high data volumes, such as event logging, audit trails, or message queues. Messaging Systems 7. : Applications requiring personalized content delivery at scale, such as content management systems, benefit from Cassandra's speed and scalability in delivering customized content to a large number of users simultaneously. Personalization and Content Management Systems 8. : Cassandra's support for multiple data centers makes it an excellent choice for applications requiring geographically distributed data. It ensures low-latency data access across different regions and provides high resilience. Geographically Distributed Applications When not to use Cassandra While Apache Cassandra is powerful and scalable, it may not be suitable for every application or use case. It is less suitable for transaction-heavy applications, complex querying, and scenarios that require strong consistency or rapid schema changes. Traditional relational database management systems (RDBMS) or other NoSQL solutions may be more appropriate in such cases. Here are several scenarios where Cassandra might : not be the optimal choice : Cassandra's complexity and resource requirements can be excessive for small-scale projects or applications with limited datasets. Simpler database solutions may offer a more cost-effective and manageable alternative. Small-Scale Projects : Cassandra does not fully support ACID (Atomicity, Consistency, Isolation, Durability) properties. If your application requires complex transactions typically found in banking or financial systems, a traditional RDBMS might be a better fit. Transactional Systems Requiring ACID Properties : If your application heavily relies on joins, subqueries, or complex aggregations, Cassandra may not be the most suitable choice. It is designed for fast writes and reads but not for complex query processing. Join Heavy Queries and Aggregations : Cassandra provides eventual consistency, which may not be suitable for use cases that require strong consistency for every read and write operation. Data with Strong Consistency Requirements : While Cassandra performs well in multi-node distributed environments, it may not be the optimal choice for single-node or small cluster deployments that require low-latency reads and writes. Low-Latency Reads and Writes in a Single Cluster : Cassandra is not optimized for storing large binary objects (blobs) such as images or videos. Other storage solutions are better suited for efficiently handling large blobs. Blob Storage : Cassandra's query capabilities are limited compared to full-fledged SQL databases. It is not well-suited for applications that heavily rely on ad-hoc querying and reporting. Applications Requiring Ad-hoc Querying In Cassandra, the design of tables is closely connected to the way data will be accessed, emphasizing the query patterns rather than solely focusing on the relationships between data entities. This differs from the approach in RDBMS, where schema design is based on normalization principles. : If your application requires frequent changes to the database schema, Cassandra's schema management may be less flexible compared to traditional RDBMS systems or other NoSQL solutions. Rapid Schema Evolution : While Cassandra is well-suited for write-heavy workloads and real-time data access, it may not be the most suitable choice for data warehousing scenarios that require complex queries, joins, and historical data analysis. Data Warehouse Applications that involve complex queries, joins, and historical data analysis Summary This article provides an overview of Cassandra, a highly scalable and distributed wide-column database. Cassandra is designed to prioritize availability and partition tolerance, making it suitable for applications where consistency is not a critical requirement. It supports high throughput and faster write operations. The building blocks of Cassandra include columns, rows, keyspaces, clusters, and nodes. Columns represent key-value pairs, rows act as containers for columns referenced by the primary key, keyspaces serve as containers for tables spanning multiple nodes, clusters contain keyspaces, and nodes refer to computer systems running Cassandra instances. Cassandra stores data in column families, which are containers for columns referenced by a primary key. Data partitioning is achieved through consistent hashing, allowing for reduced latency and increased throughput. The partitioner distributes data across the Consistent Hash ring, and a coordinator node handles read and write queries. Cassandra provides replication for high availability. Replicas of data are stored on multiple nodes, ensuring that queries can be handled by replicas if a node becomes unavailable. Replication factors and strategies determine the number of replicas and the nodes responsible for them. While Cassandra offers benefits such as scalability and high availability, it has limitations. It does not support table joins, foreign keys, or the ability to add columns other than the primary key in the WHERE clause during querying. Overall, Cassandra is a powerful database solution for highly scalable applications, particularly those that prioritize availability and partition tolerance over strong consistency. There are several interesting aspects of Cassandra that I will cover in my next article. so you don't miss it! Subscribe to me Cheers!

Cassandra: Highly Scalable Database Out of the Box

ক্যাসান্ড্রা: বাক্সের বাইরে উচ্চ মাত্রার ডেটাবেস

Cassandra: Hochskalierbare Datenbank sofort einsatzbereit

Cassandra: base de datos altamente escalable lista para usar

Cassandra : base de données hautement évolutive prête à l'emploi

कैसेंड्रा: बॉक्स से बाहर अत्यधिक स्केलेबल डेटाबेस

Cassandra: すぐに使える拡張性の高いデータベース

Cassandra: 즉시 사용 가능한 확장성이 뛰어난 데이터베이스

Cassandra: banco de dados altamente escalável pronto para uso

Cassandra: масштабируемая база данных «из коробки»

Cassandra: Kullanıma Hazır Yüksek Derecede Ölçeklenebilir Veritabanı

Cassandra: Cơ sở dữ liệu có khả năng mở rộng cao ngay lập tức

Cassandra：开箱即用的高度可扩展数据库

This paper is available on arxiv under CC 4.0 license. . Authors: Gemini Team, Google Table of Links Abstract and Introduction Model Architecture Training Infrastructure Training Dataset Evaluation Responsible Deployment Discussion and Conclusion, References Contributions and Acknowledgments Appendix This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks — notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of Gemini models in cross-modal reasoning and language understanding will enable a wide variety of use cases and we discuss our approach toward deploying them responsibly to users. 1. Introduction We present Gemini, a family of highly capable multimodal models developed at Google. We trained Gemini jointly across image, audio, video, and text data for the purpose of building a model with both strong generalist capabilities across modalities alongside cutting-edge understanding and reasoning performance in each respective domain. Gemini 1.0, our first version, comes in three sizes: Ultra for highly-complex tasks, Pro for enhanced performance and deployability at scale, and Nano for on-device applications. Each size is specifically tailored to address different computational limitations and application requirements. We evaluate the performance of Gemini models on a comprehensive suite of internal and external benchmarks covering a wide range of language, coding, reasoning, and multimodal tasks. Gemini advances state-of-the-art in large-scale language modeling (Anil et al., 2023; Brown et al., 2020; Chowdhery et al., 2023; Hoffmann et al., 2022; OpenAI, 2023a; Radford et al., 2019; Rae et al., 2021), image understanding (Alayrac et al., 2022; Chen et al., 2022; Dosovitskiy et al., 2020; OpenAI, 2023b; Reed et al., 2022; Yu et al., 2022a), audio processing (Radford et al., 2023; Zhang et al., 2023), and video understanding(Alayrac et al., 2022; Chen et al., 2023). It also builds on the work on sequence models (Sutskever et al., 2014), a long history of work in deep learning based on neural networks (LeCun et al., 2015), and machine learning distributed systems (Barham et al., 2022; Bradbury et al., 2018; Dean et al., 2012) that enable large-scale training. Our most capable model, Gemini Ultra, achieves new state-of-the-art results in 30 of 32 benchmarks we report on, including 10 of 12 popular text and reasoning benchmarks, 9 of 9 image understanding benchmarks, 6 of 6 video understanding benchmarks, and 5 of 5 speech recognition and speech translation benchmarks. Gemini Ultra is the first model to achieve human-expert performance on MMLU (Hendrycks et al., 2021a) — a prominent benchmark testing knowledge and reasoning via a suite of exams — with a score above 90%. Beyond text, Gemini Ultra makes notable advances on challenging multimodal reasoning tasks. For example, on the recent MMMU benchmark (Yue et al., 2023), that comprises questions about images on multi-discipline tasks requiring college-level subject knowledge and deliberate reasoning, Gemini Ultra achieves a new state-of-the-art score of 62.4%, outperforming the previous best model by more than 5 percentage points. It provides a uniform performance lift for video question answering and audio understanding benchmarks. Qualitative evaluation showcases impressive crossmodal reasoning capabilities, enabling the model to understand and reason across an input sequence of audio, images, and text natively (see Figure 5 and Table 13). Consider the educational setting depicted in Figure 1 as an example. A teacher has drawn a physics problem of a skier going down a slope, and a student has worked through a solution to it. Using Gemini’s multimodal reasoning capabilities, the model is able to understand the messy handwriting, correctly understand the problem formulation, convert both the problem and solution to mathematical typesetting, identify the specific step of reasoning where the student went wrong in solving the problem, and then give a worked through correct solution to the problem. This opens up exciting educational possibilities, and we believe the new multimodal and reasoning capabilities of Gemini models have dramatic applications across many fields. The reasoning capabilities of large language models show promise toward building generalist agents that can tackle more complex multi-step problems. The AlphaCode team built AlphaCode 2 (Leblond et al, 2023), a new Gemini-powered agent, that combines Gemini’s reasoning capabilities with search and tool-use to excel at solving competitive programming problems. AlphaCode 2 ranks within the top 15% of entrants on the Codeforces competitive programming platform, alarge improvement over its state-of-the-art predecessor in the top 50% (Li et al., 2022). In tandem, we advance the frontier of efficiency with Gemini Nano, a series of small models targeting on-device deployment. These models excel in on-device tasks, such as summarization, reading comprehension, text completion tasks, and exhibit impressive capabilities in reasoning, STEM, coding, multimodal, and multilingual tasks relative to their sizes. In the following sections, we first provide an overview of the model architecture, training infrastructure, and training dataset. We then present detailed evaluations of the Gemini model family, covering well-studied benchmarks and human-preference evaluations across text, code, image, audio and video — which include both English performance and multilingual capabilities. We also discuss our approach to responsible deployment, [2] including our process for impact assessments, developing model policies, evaluations, and mitigations of harm before deployment decisions. Finally, we discuss the broader implications of Gemini, its limitations alongside its potential applications — paving the way for a new era of research and innovation in AI. [2] We plan to update this report with more details ahead of the general availability of the Gemini Ultra model.

Gemini - A Family of Highly Capable Multimodal Models: Abstract and Introduction

মিথুন - অত্যন্ত সক্ষম মাল্টিমোডাল মডেলের একটি পরিবার: বিমূর্ত এবং ভূমিকা

Gemini – Eine Familie hochleistungsfähiger multimodaler Modelle: Zusammenfassung und Einführung

Gemini: una familia de modelos multimodales de gran capacidad: resumen e introducción

Gemini - Une famille de modèles multimodaux hautement performants : résumé et introduction

जेमिनी - अत्यधिक सक्षम मल्टीमॉडल मॉडल का परिवार: सार और परिचय

Gemini - 高度な機能を備えたマルチモーダル モデルのファミリー: 要約と概要

Gemini - 고성능 다중 모드 모델 제품군: 개요 및 소개

Gemini – Uma Família de Modelos Multimodais Altamente Capazes: Resumo e Introdução

Gemini — семейство высокопроизводительных мультимодальных моделей: краткое содержание и введение

Gemini - Son Derece Yetenekli Multimodal Modellerden Oluşan Bir Aile: Özet ve Giriş

Gemini - Một nhóm các mô hình đa phương thức có khả năng cao: Tóm tắt và giới thiệu

Gemini - 一系列高性能多模式模型：摘要和简介

It’s not a secret that in recent years Infrastructure as a Service and Platform as a Service have become increasingly widespread on various projects due to their capabilities, particularly resource efficiency and flexibility. As a result, Microsoft spent a lot of time and effort creating a user-friendly environment in which SQL can be used. Social Discovery Group team uses a variety of databases including SQL to power our products. With a portfolio of 40+ global services that help to meet and connect worldwide, our user base includes over 250 million people across the globe. To guarantee the reliability of our products for the users, we keep part of the key infrastructure in the cloud. This helps to enhance its resilience, security, and flexibility. We’re quite experienced in deploying server and service databases on various platforms, including Kubernetes clusters. However, we faced the need to make a part of the related SQL databases infrastructure in the Azure cloud as flexible, efficient, and reliable as possible. There are 3 ways to use SQL in the Microsoft Azure cloud: Azure SQL Database Azure SQL Managed Instance SQL Server on Azure Virtual Machines After the research, we’ve decided to use Azure SQL databases. Just to clarify for those who have never heard of so-called Azure SQL databases, they are managed cloud databases provided as part of Microsoft Azure. I have highlighted the following benefits: There is no need to worry about updates or end-of-life support; Easy configuration and deployment; Speed of deployment (and therefore development) and scalability; High availability; Fault tolerance; Ease of backup; Cost optimization; An integrated Microsoft Azure monitoring system. Now let's talk about things step by step and take a look at the process of deploying and creating a database. This can be done using a Power Shell script or the Azure CLI, but for the sake of clarity, I look at the process using the portal's graphical interface. To do this, go to Azure SQL, click 'Create', and select 'SQL Databases'. We specify the resource group, select whether there is an existing server or create a new one (indicating the administrator’s name and data), and come up with a name for the database. I’d recommend choosing DTU (database transaction unit) based bundled packages with a balanced mix of compute and storage resources for our common workloads. There are also some tabs for settings: Network, Security, Additional settings, and Tags; for a minimum standard configuration, these can be left unchanged by default. Then we wait for the database to be created. This completes the minimum setup, and the base is done. The size of the database resources can be changed super easily, literally with a click, and in case of insufficient resources, we can set the parameters we need in terms of size and performance. Then you can connect to your database in any way you prefer from the outside, without forgetting to add your IP address or subnet, or to allow all connections in the firewall of the server on which this database is hosted. It’s convenient to connect and further manage through SQL Server Management Studio (SSMS), but it is also possible to do so through other tools and the Azure portal itself. In addition to a public connection point, you can also create a private one by adding a server to the required subnet and configuring private DNS zones. Speaking about fault tolerance, here we see a very convenient and intuitive implementation of failover, a group of protecting servers based in different regions. In Azure, it’s possible to add and remove databases on servers in a failover group, forced failover, and automatic failover mode. You can see this in the screenshot below. Let's come up with a name for the failover group and put the server into failover. Synchronization of the specified databases will start automatically. The second server will be in read-only mode. In the event of a failure, traffic is automatically switched to the second region, and the primary and secondary servers automatically switch places. But failover will not help if there is a data-level problem in the databases themselves. For sure in this case, you need to create backups. It’s possible to configure backups both within the portal and through third-party tools or, for example, Azure DevOps (in the pipeline you can use the SqlAzureDacpacDeployment + AzureFileCopy task). Within the portal, backups are configured on the Backups tab and the necessary storage policies are set. If you prefer to use third-party backup tools, I would recommend considering Azure DevOps or SQL package tools. The recovery process on the portal itself is not very convenient in my opinion. The first thing you notice is the long recovery time for simple test databases. For example, it took me more than half an hour to restore a 30MB basic-size database from yesterday's backup! After contacting Microsoft Azure support, I was advised to use PowerShell scripts for recovery and notified that the database size should be at least S3 for the recovery process, and later the size could be reduced. Below I’m going to present some of my scripts and developments on this subject, they can be improved and enhanced but I am sure many of you can find them useful. I'll take you step by step: In case you don't have PowerShell ISE installed on Windows, download it here: https://github.com/PowerShell/Pohell/releases/download/v7.3.0/PowerShell-7.3.0-win-x64.msi https://github.com/PowerShell/PowerShell/releases/download/v7.3.0/PowerShell-7.3.0-win-x86.msi Next, you need to install the Azure module: Install-Module Az After installing the AZ module, import the AZ module: Import-Module Az Once imported, you can connect to your Azure account: Connect-AzAccount. A popup will appear to log into your Azure account, then you will be connected Run the PowerShell script itself. “ #Variables in use

$Database = Get-AzSqlDatabase -ResourceGroupName "Test" -ServerName "test-serv1" -DatabaseName "dbforscript"

$TargetDB = "dbforscript_new" 

$PITRtimedate = "2022-12-02 10:00:00Z" ##вам нужно увидеть действительную дату и время  на портале

$PITRSLO = "S3" 

$PITRNEWSLO = "S0" 

$PITRedition = "Standard" 

$failoverGroupRG = "Test"  

$failoverGroupS = "test-serv1" 

$failoverGroupDB = "dbforscript" 

$removedbfromfgRG = "Test" 

$removedbfromfgS = "test-serv1" 

$removedbfromfgDB = "XXXXX"

$dropreplicaRG = "Test"

$dropreplicaS = "test-serv2"

$dropreplicaDB = "dbforscript"

$sourcedbRG = "Test"

$sourcedbS = "test-serv1"

$sourcedbDBname = "dbforscript"

$sourcedbDBNEWname = "dbforscript_old" 

$TargetDBNEWname = "dbforscript" “ 1 - This code initiates a database restore with a different name. If the original name of the database being restored is "dbforscript", then the name of the restored database will be dbforscript_new. The restored database will be SLO version S3 or higher, which is the recommended way to perform this action, the variable for this is $PITRSLO = "S3", you can use S3 or higher. After this we will reset the SLO level to the original one, this is for recovery only. “Restore-AzSqlDatabase -FromPointInTimeBackup -PointInTime $PITRtimedate -ResourceGroupName $Database.ResourceGroupName -ServerName $Database.ServerName -TargetDatabaseName $TargetDB -ResourceId $Database.ResourceID -Edition $PITRedition -ServiceObjectiveName $PITRSLO” 2 - This code will remove the source database from the failover group: source database: dbforscript. “$failoverGroup = Get-AzSqlDatabase -ResourceGroupName $failoverGroupRG -ServerName $failoverGroupS -DatabaseName $failoverGroupdb | Remove-AzSqlDatabaseFromFailoverGroup -ResourceGroupName $removedbfromfgRG -ServerName $removedbfromfgS -FailoverGroupName $removedbfromfgDB” 3 - This code will remove the replica database from the server where it is located: dbforscript on the test-serv2 server. “Remove-AzSqlDatabase -ResourceGroupName $dropreplicaRG -ServerName $dropreplicaS -DatabaseName $dropreplicaDB” 4 - This code will rename the original database to a different name: after the renaming, dbforscript will be dbforscript_old. “Set-AzSqlDatabase -ResourceGroupName $sourcedbRG -DatabaseName $sourcedbDBname -ServerName $sourcedbS -NewName $sourcedbDBNEWname” 5 - This code will rename the restored database to the original database name, renaming dbforscript_new to dbforscript. “Set-AzSqlDatabase -ResourceGroupName $Database.ResourceGroupName -DatabaseName $TargetDB -ServerName $Database.ServerName -NewName $TargetDBNEWname” 6 - This code will return your database SLO level to the previous (original) S0 value. if your database is basic, please you can upgrade from S0 to basic after in the portal. “Set-AzSqlDatabase -ResourceGroupName $Database.ResourceGroupName -DatabaseName $TargetDBNEWname -ServerName $Database.ServerName -Edition $PITRedition -RequestedServiceObjectiveName $PITRNEWSLO -MaxSizeBytes 10737418240” 7 - The last code adds the restored database to the failover group, which already has the original name (since we changed it in the previous code). “$failoverGroup = Get-AzSqlDatabase -ResourceGroupName $failoverGroupRG -ServerName $failoverGroupS -DatabaseName $TargetDBNEWname | Add-AzSqlDatabaseToFailoverGroup -ResourceGroupName $failoverGroupRG -ServerName $failoverGroupS -FailoverGroupName $removedbfromfgDB” You can consider adding the - ErrorAction Stop parameter after the command. This will prevent the following commands from being executed in the event of an error, and there will be no snowballing. Also, you can add Get-Date at the beginning and end of the script to calculate the execution time. In my case, a database of about 3.3 GB was restored by such a script in less than 6 minutes. If you wish, you can surely optimize the script, add it via Azure DevOps, reduce the number of variables, or hardcode something, but I have tried to describe it in as much detail as possible and in a way that everyone can understand. Database monitoring on Azure and the ability to integrate with various systems, such as Datadog, deserves special attention. Monitoring is quite convenient, but not without nuances (at the time of writing, for example, read-only users could only see monitoring for one database, not all at once... well here are the shades). In conclusion, our team has successfully optimized expenses while also addressing concerns related to updates and support discontinuation. We achieved improvements in performance, resilience, development speed, and flexibility. Additionally, the implementation of scripts has notably enhanced our ability to recover swiftly when needed.

Unlocking Azure: How to Build a Highly Flexible SQL Database Infrastructure

Azure আনলক করা: কিভাবে একটি উচ্চ নমনীয় SQL ডাটাবেস পরিকাঠামো তৈরি করা যায়

Azure freischalten: So bauen Sie eine hochflexible SQL-Datenbank-Infrastruktur auf

Desbloqueo de Azure: cómo construir una infraestructura de base de datos SQL altamente flexible

Déverrouiller Azure : comment créer une infrastructure de base de données SQL hautement flexible

Azure को अनलॉक करना: अत्यधिक लचीले SQL डेटाबेस इन्फ्रास्ट्रक्चर का निर्माण कैसे करें

Azure のロックを解除する: 柔軟性の高い SQL データベース インフラストラクチャを構築する方法

Azure 활용: 매우 유연한 SQL 데이터베이스 인프라를 구축하는 방법

Desbloqueando o Azure: como construir uma infraestrutura de banco de dados SQL altamente flexível

Разблокировка Azure: как построить высокогибкую инфраструктуру базы данных SQL

Azure'un Kilidini Açma: Son Derece Esnek Bir SQL Veritabanı Altyapısı Nasıl Oluşturulur

Mở khóa Azure: Cách xây dựng cơ sở hạ tầng cơ sở dữ liệu SQL có tính linh hoạt cao

解锁 Azure：如何构建高度灵活的 SQL 数据库基础架构

Okay, okay. It's not that suspicious. It's obvious that China's TikTok really wants a piece of that sweet, sweet social media pie. Enough to add a new feature, to the wildly successful video sharing app (and the key to fame of countless creators), that already exists in other social media apps, specifically Meta's Instagram. Texts. That's the feature. Texts. Allow us to elaborate. TikTok is primarily a video-sharing social media app, but with the introduction of text posts, users can now make/share.. Text-only posts (see below). In effect, letting users publish text-only posts is no different than what users can already do on platforms like Instagram, but tech publications are reporting that the timing coincides with what is perhaps the downfall of Elon Musk's Twitter/X/__Everything__™ app. Major tech companies are trying to capitalize on the turmoil caused by Murk's purchase of the company last year and woo advertisers on to their platform by offering similar functionality to brands looking to shove their products down consumers' throats 😇. TikTok is not an exception. Given how poorly X, formerly known as Twitter, is doing in terms of revenue and profitability, it's no wonder that its competitors are circling around the app like sharks looking for blood. Mark Zukckerberg's Meta drew first blood with the launch of Threads (which was by no means the first microblogging app to challenge Twitter's dominance), but Zuck's platform has run into its own set of issues in terms of keeping users engaged (lol). X's problems are by no means limited to its books. Musk's rebranding of Twitter is going as well as you'd expect it to: take, for example, the fact that Meta, Microsoft, and countless others already hold the intellectual property rights to the letter 'X', or the heat Musk is receiving for installing a giant 'X' logo at Twitter 'X' HQ, drawing flak from San Francisco residents and ultimately resulting in its removal. That said, 'X's monthly users have reached a new high of over half a billion people, Musk recently tweeted (or X'd idk). In contrast, users are already leaving Zuckerberg's Threads in droves, prompting the company to consider adding more "retention-driving hooks" to entice them to return to the app, including by using AI-powered chatbots, Reuters reported. But while Meta might be failing at Threads, it is certainly not failing at Reels, Meta's answer to TikTok. According to figures released by the company this past week, Reels videos are growing rapidly among both users and advertisers and are quickly catching up to the ByteDance-owned TikTok app. Meta says the rags-to-riches growth of Reels, which are viewable on both Facebook and Instagram, speaks in part to the company's improving recommendation software, long the Chinese-owned rival's strong point, Reuters wrote. Phew, what a week. TikTok ranked #64 on HackerNoon's Tech Company Rankings this week. Facebook was on the #4 spot, while Instagram was on #2. 👋 You’re reading part 1 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 2 goes live tomorrow. Hate waiting? No problemo! Just subscribe here to receive the complete newsletter a day early in your inbox. In Other News.. 📰 Sony PlayStation 5 console sales pass 40 million — via Reuters.
LinkedIn seems to be working on an AI ‘coach’ for job applications — via The Verge.
Zuck Says He's 'Not Sure' if the Elon Cage Match Will Happen — via Gizmodo.
Twitter, now X, threatens suit against nonprofit studying hate speech and misinformation — via CNBC.
OpenAI’s head of trust and safety is stepping down — via CNN.
Scoop: Google Assistant to get an AI makeover — via Axios. And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon Okay, okay. It's not that suspicious. that It's obvious that China's TikTok really wants a piece of that sweet, sweet social media pie. Enough to add a new feature, to the wildly successful video sharing app (and the key to fame of countless creators), that already exists in other social media apps, specifically Meta 's Instagram . TikTok TikTok Meta Meta Instagram Instagram Texts . That's the feature. Texts. Texts Allow us to elaborate. TikTok is primarily a video-sharing social media app, but with the introduction of text posts, users can now make/share.. Text-only posts (see below). introduction introduction In effect, letting users publish text-only posts is no different than what users can already do on platforms like Instagram, but tech publications are reporting that the timing coincides with what is perhaps the downfall of Elon Musk's Twitter / X /__ Everything __™ app. Major tech companies are trying to capitalize on the turmoil caused by Murk's purchase of the company last year and woo advertisers on to their platform by offering similar functionality to brands looking to shove their products down consumers' throats 😇. reporting reporting Twitter Twitter X X Everything TikTok is not an exception. Given how poorly X, formerly known as Twitter, is doing in terms of revenue and profitability, it's no wonder that its competitors are circling around the app like sharks looking for blood. Mark Zukckerberg's Meta drew first blood with the launch of Threads (which was by no means the first microblogging app to challenge Twitter's dominance), but Zuck's platform has run into its own set of issues in terms of keeping users engaged (lol). set of issues set of issues X's problems are by no means limited to its books . Musk's rebranding of Twitter is going as well as you'd expect it to: take, for example, the fact that Meta, Microsoft, and countless others already hold the intellectual property rights to the letter 'X', or the heat Musk is receiving for installing a giant 'X' logo at Twitter 'X' HQ, drawing flak from San Francisco residents and ultimately resulting in its removal. limited to its books limited to its books hold hold drawing flak drawing flak resulting resulting That said, 'X's monthly users have reached a new high of over half a billion people, Musk recently tweeted (or X 'd idk). tweeted tweeted X In contrast, users are already leaving Zuckerberg's Threads in droves, prompting the company to consider adding more "retention-driving hooks" to entice them to return to the app, including by using AI-powered chatbots, Reuters reported . But while Meta might be failing at Threads, it is certainly not failing at Reels, Meta's answer to TikTok. using using reported reported According to figures released by the company this past week, Reels videos are growing rapidly among both users and advertisers and are quickly catching up to the ByteDance-owned TikTok app. Meta says the rags-to-riches growth of Reels, which are viewable on both Facebook and Instagram, speaks in part to the company's improving recommendation software, long the Chinese-owned rival's strong point, Reuters wrote . wrote wrote Phew, what a week. TikTok ranked #64 on HackerNoon's Tech Company Rankings this week. Facebook was on the #4 spot, while Instagram was on #2. TikTok TikTok Facebook Facebook Instagram Instagram 👋 You’re reading part 1 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 2 goes live tomorrow. Hate waiting? No problemo! Just subscribe here to receive the complete newsletter a day early in your inbox. 👋 You’re reading part 1 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 2 goes live tomorrow. Hate waiting? No problemo! Just subscribe here to receive the complete newsletter a day early in your inbox. You’re reading part 1 of HackerNoon's Tech Company News Brief, a weekly collection of tech goodness that combines HackerNoon's proprietary data with internet trends to determine which companies are rising and falling in the public consciousness. Part 2 goes live tomorrow. Hate waiting? No problemo! Just subscribe here to receive the complete newsletter a day early in your inbox. part 1 Part 2 here complete In Other News.. 📰 In Other News.. 📰 Sony PlayStation 5 console sales pass 40 million — via Reuters. LinkedIn seems to be working on an AI ‘coach’ for job applications — via The Verge. Zuck Says He's 'Not Sure' if the Elon Cage Match Will Happen — via Gizmodo. Twitter, now X, threatens suit against nonprofit studying hate speech and misinformation — via CNBC. OpenAI’s head of trust and safety is stepping down — via CNN. Scoop: Google Assistant to get an AI makeover — via Axios. Sony PlayStation 5 console sales pass 40 million — via Reuters . Reuters Reuters LinkedIn seems to be working on an AI ‘coach’ for job applications — via The Verge . The Verge The Verge Zuck Says He's 'Not Sure' if the Elon Cage Match Will Happen — via Gizmodo . Gizmodo Gizmodo Twitter, now X, threatens suit against nonprofit studying hate speech and misinformation — via CNBC . CNBC CNBC OpenAI’s head of trust and safety is stepping down — via CNN . CNN CNN Scoop: Google Assistant to get an AI makeover — via Axios . Axios Axios And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon — Sheharyar Khan, Editor, Business Tech @ HackerNoon

Timing of TikTok's New Feature Highly Suspicious 🤔🤔🤔

TikTok এর নতুন বৈশিষ্ট্যের সময় অত্যন্ত সন্দেহজনক 🤔🤔🤔

Zeitpunkt der neuen Funktion von TikTok höchst verdächtig 🤔🤔🤔

Momento de la nueva función de TikTok altamente sospechosa 🤔🤔🤔

Le moment de la nouvelle fonctionnalité de TikTok est très suspect 🤔🤔🤔

टिकटॉक के नए फीचर की टाइमिंग बेहद संदिग्ध 🤔🤔🤔

TikTokの新機能のタイミングは非常に疑わしい 🤔🤔🤔

TikTok의 새로운 기능의 타이밍은 매우 의심스럽습니다 🤔🤔🤔

Momento do novo recurso do TikTok altamente suspeito 🤔🤔🤔

TikTok'un Yeni Özelliğinin Zamanlaması Oldukça Şüpheli 🤔🤔🤔

Thời điểm ra mắt tính năng mới của TikTok Rất đáng ngờ 🤔🤔🤔

TikTok 新功能的时机非常可疑🤔🤔🤔

**SINGAPORE, Singapore, August 5th, 2024/Chainwire/--**Hybrid cryptocurrency exchange GRVT (pronounced “gravity”), ZKsync’s first official Validium ZK Chain, launches its Open Beta Testnet today. After months of anticipation, the 2.5 million waitlisted testers can now experience GRVT’s cutting-edge features. Blending the strengths of both CEXs and DEXs, GRVT empowers users with self-custody of their assets and offers off-chain order matching combined with on-chain settlements at an impressive 600,000 transactions per second (TPS). This unique model ensures that transactions benefit from the speed of off-chain processes, while all asset settlements remain secure and verifiable on the blockchain. To celebrate the Open Beta Testnet launch, GRVT offers exclusive rewards to early participants: Be among the first 30,000 users to complete KYC verification and win from a pool of 2.4 million $ZK tokens and 600,000 raffle tickets.


Claim raffle tickets immediately upon verification.


To claim $ZK tokens, participate on Mainnet Day 1 (more details about Mainnet will be announced later). “GRVT aims to revolutionize financial markets by integrating blockchain technology and self-custody solutions into both TradFi and DeFi,” said Hong Yea, Co-Founder and CEO of GRVT. “We are thrilled to open our platform to the public. By applying blockchain settlement and trustless risk management to centralized order book infrastructure, GRVT is transforming trading and investment while upholding traditional security controls. I believe this approach, starting with crypto markets, can reshape the entire financial landscape.” GRVT’s development is backed by Matter Labs, the creator of ZKsync, along with support from prominent industry partners and investors, including Delphi Ventures, Matrix Partners, Hack VC, ABCDE Capital and so on. For more information and to join the GRVT community, users can visit grvt.io. Disclaimer: Cryptocurrencies carry high risks. This content is not a distribution of, or an offer or solicitation to provide, financial services or products, nor a representation as to their suitability or legality for you. GRVT is not a regulated entity and your funds are not subject to regulatory protection. Before making any decision based on this content, please seek financial and legal advice, and carefully review our [Risk Disclosure and Disclaimer] in full. Singapore users: GRVT is not licensed, approved, authorised, designated, recognised, registered or otherwise regulated under any legislation administered by the Monetary Authority of Singapore ("MAS"). As such, users will not have the benefit of any regulatory safeguards imposed by the MAS. About GRVT GRVT (pronounced “gravity”) is a hybrid derivatives exchange enabling off-chain order matching and on-chain settlements at 600,000 TPS. Founded in 2022 and backed by Matter Labs, GRVT is ZKsync’s first official Validium ZK Chain. Our mission is to democratize the financial market with secure, self-custodial solutions, providing a safe, efficient and simple trading environment for everyone. GRVT official website For media inquiries, contact: press@grvt.io Social and Community: X | LinkedIn | Telegram | Discord Contact Reed Li GRVT press@grvt.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **SINGAPORE, Singapore, August 5th, 2024/Chainwire/--**Hybrid cryptocurrency exchange GRVT (pronounced “gravity”), ZKsync’s first official Validium ZK Chain, launches its Open Beta Testnet today. After months of anticipation, the 2.5 million waitlisted testers can now experience GRVT’s cutting-edge features. Blending the strengths of both CEXs and DEXs, GRVT empowers users with self-custody of their assets and offers off-chain order matching combined with on-chain settlements at an impressive 600,000 transactions per second (TPS). This unique model ensures that transactions benefit from the speed of off-chain processes, while all asset settlements remain secure and verifiable on the blockchain. To celebrate the Open Beta Testnet launch, GRVT offers exclusive rewards to early participants: Be among the first 30,000 users to complete KYC verification and win from a pool of 2.4 million $ZK tokens and 600,000 raffle tickets. Claim raffle tickets immediately upon verification. To claim $ZK tokens, participate on Mainnet Day 1 (more details about Mainnet will be announced later). Be among the first 30,000 users to complete KYC verification and win from a pool of 2.4 million $ZK tokens and 600,000 raffle tickets. Be among the first 30,000 users to complete KYC verification and win from a pool of 2.4 million $ZK tokens and 600,000 raffle tickets. Claim raffle tickets immediately upon verification. Claim raffle tickets immediately upon verification. To claim $ZK tokens, participate on Mainnet Day 1 (more details about Mainnet will be announced later). To claim $ZK tokens, participate on Mainnet Day 1 (more details about Mainnet will be announced later). “GRVT aims to revolutionize financial markets by integrating blockchain technology and self-custody solutions into both TradFi and DeFi,” said Hong Yea, Co-Founder and CEO of GRVT. “We are thrilled to open our platform to the public. By applying blockchain settlement and trustless risk management to centralized order book infrastructure, GRVT is transforming trading and investment while upholding traditional security controls. I believe this approach, starting with crypto markets, can reshape the entire financial landscape.” “GRVT aims to revolutionize financial markets by integrating blockchain technology and self-custody solutions into both TradFi and DeFi,” said Hong Yea, Co-Founder and CEO of GRVT. “We are thrilled to open our platform to the public. By applying blockchain settlement and trustless risk management to centralized order book infrastructure, GRVT is transforming trading and investment while upholding traditional security controls. I believe this approach, starting with crypto markets, can reshape the entire financial landscape.” GRVT’s development is backed by Matter Labs, the creator of ZKsync, along with support from prominent industry partners and investors, including Delphi Ventures, Matrix Partners, Hack VC, ABCDE Capital and so on. For more information and to join the GRVT community, users can visit grvt.io . grvt.io grvt.io Disclaimer: Cryptocurrencies carry high risks. This content is not a distribution of, or an offer or solicitation to provide, financial services or products, nor a representation as to their suitability or legality for you. GRVT is not a regulated entity and your funds are not subject to regulatory protection. Before making any decision based on this content, please seek financial and legal advice, and carefully review our [Risk Disclosure and Disclaimer] in full. Singapore users: GRVT is not licensed, approved, authorised, designated, recognised, registered or otherwise regulated under any legislation administered by the Monetary Authority of Singapore ("MAS"). As such, users will not have the benefit of any regulatory safeguards imposed by the MAS. About GRVT GRVT (pronounced “gravity”) is a hybrid derivatives exchange enabling off-chain order matching and on-chain settlements at 600,000 TPS. Founded in 2022 and backed by Matter Labs, GRVT is ZKsync’s first official Validium ZK Chain. Our mission is to democratize the financial market with secure, self-custodial solutions, providing a safe, efficient and simple trading environment for everyone. GRVT GRVT GRVT official website GRVT official website For media inquiries, contact: press@grvt.io press@grvt.io press@grvt.io Social and Community: X | LinkedIn | Telegram | Discord X X LinkedIn LinkedIn Telegram Telegram Discord Discord Contact Reed Li GRVT press@grvt.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

ZKsync-Powered GRVT’s Highly Anticipated Open Beta Goes Live Today

ZKsync-চালিত GRVT-এর উচ্চ প্রত্যাশিত ওপেন বিটা আজ লাইভ হয়

Die mit Spannung erwartete offene Betaversion von GRVT auf ZKsync-Basis geht heute online

La muy esperada beta abierta de GRVT impulsada por ZKsync se lanza hoy

La bêta ouverte très attendue de GRVT propulsée par ZKsync est lancée aujourd'hui

ZKsync-संचालित GRVT का बहुप्रतीक्षित ओपन बीटा आज लाइव हो गया

ZKsync 搭載 GRVT の待望のオープンベータが本日公開

ZKsync 기반 GRVT의 매우 기대되는 오픈 베타가 오늘 출시됩니다

O altamente antecipado beta aberto do GRVT com tecnologia ZKsync vai ao ar hoje

Долгожданная открытая бета-версия GRVT на базе ZKsync выходит сегодня

ZKsync Destekli GRVT'nin Merakla Beklenen Açık Betası Bugün Yayına Başlıyor

Phiên bản beta mở rất được mong đợi của GRVT được hỗ trợ bởi ZKsync sẽ ra mắt ngay hôm nay

由 ZKsync 提供支持的 GRVT 备受期待的公开测试版今日上线

Here's Why Talent Isn't Rare. This Is.

The Dubai Multi Commodities Centre (DMCC) and cryptocurrency exchange Bybit have announced the second edition of their collaborative hackathon, "DMCC x Bybit Web3 Unleashed." Set to take place from September 1 to November 20, 2024, this event aims to bring together developers, tech pioneers, and investors from around the world to tackle real-world problems using Web3 technologies. The hackathon, which will culminate in a live pitch event at a prestigious Dubai hotel, offers participants the opportunity to showcase their projects on a global stage. With a substantial prize pool of up to 100,000 USDT in cash and services, the event is poised to attract top talent from across the Web3 ecosystem. Participants will explore a diverse range of cutting-edge topics, including artificial intelligence, infrastructure development, zero-knowledge proofs, digital identity solutions, and decentralized physical infrastructure networks (DEPIN). This broad scope reflects the organizers' commitment to addressing complex, multifaceted challenges through innovative technological approaches. The event's structure is designed to foster both depth and breadth of innovation. Following a registration period that closes on October 5, projects will undergo a rigorous preliminary screening process. The top 10 finalists, to be announced on October 21, will earn the prestigious opportunity to pitch their projects live in Dubai on November 20. Industry experts have noted that events like these play a crucial role in driving innovation and addressing real-world problems in the rapidly evolving Web3 landscape. By bringing together diverse talents and fostering collaboration, this hackathon has the potential to spark breakthroughs that could shape the future of technology and its applications across various sectors. The involvement of high-profile partners and judges, including DWF Labs, Hacken, Injective, Meezan Ventures, and Cointelegraph, further elevates the event's stature. These industry heavyweights bring a wealth of expertise and connections, offering participants unparalleled opportunities for networking and professional growth. While some observers have pointed out the challenges of translating hackathon innovations into real-world applications, the organizers have taken proactive steps to address this concern. By involving industry partners and offering ongoing support services to winners, the event aims to create a bridge between innovative ideas and practical implementation. This approach not only enhances the long-term impact of the hackathon but also provides a valuable model for future events in the Web3 space. The "DMCC x Bybit Web3 Unleashed" hackathon represents a significant step forward in the global effort to harness the power of Web3 technologies for societal benefit. By focusing on real-world problem-solving and bringing together a diverse array of stakeholders, the event has the potential to catalyze meaningful innovation in the Web3 space. As the Web3 ecosystem continues to evolve and mature, events like these will likely play an increasingly important role in shaping its trajectory. The success of this hackathon could serve as a model for future collaborative efforts aimed at leveraging emerging technologies to address pressing global challenges. The organizers' commitment to fostering ongoing development and implementation of winning projects demonstrates a forward-thinking approach to innovation. This holistic strategy not only enhances the value of the hackathon for participants but also increases the likelihood of generating lasting, impactful solutions to real-world problems. As the Web3 industry continues to grow and evolve, events like the "DMCC x Bybit Web3 Unleashed" hackathon will be crucial in driving innovation, fostering collaboration, and ultimately shaping the future of technology. With its focus on real-world applications and strong industry support, this event stands as a beacon of progress in the ongoing development of the Web3 ecosystem. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR The Dubai Multi Commodities Centre (DMCC) and cryptocurrency exchange Bybit have announced the second edition of their collaborative hackathon, "DMCC x Bybit Web3 Unleashed." Set to take place from September 1 to November 20, 2024, this event aims to bring together developers, tech pioneers, and investors from around the world to tackle real-world problems using Web3 technologies. Dubai Multi Commodities Centre Bybit The hackathon, which will culminate in a live pitch event at a prestigious Dubai hotel, offers participants the opportunity to showcase their projects on a global stage. With a substantial prize pool of up to 100,000 USDT in cash and services, the event is poised to attract top talent from across the Web3 ecosystem. Participants will explore a diverse range of cutting-edge topics, including artificial intelligence, infrastructure development, zero-knowledge proofs, digital identity solutions, and decentralized physical infrastructure networks (DEPIN). This broad scope reflects the organizers' commitment to addressing complex, multifaceted challenges through innovative technological approaches. The event's structure is designed to foster both depth and breadth of innovation. Following a registration period that closes on October 5, projects will undergo a rigorous preliminary screening process. The top 10 finalists, to be announced on October 21, will earn the prestigious opportunity to pitch their projects live in Dubai on November 20. Industry experts have noted that events like these play a crucial role in driving innovation and addressing real-world problems in the rapidly evolving Web3 landscape. By bringing together diverse talents and fostering collaboration, this hackathon has the potential to spark breakthroughs that could shape the future of technology and its applications across various sectors. The involvement of high-profile partners and judges, including DWF Labs, Hacken, Injective, Meezan Ventures, and Cointelegraph, further elevates the event's stature. These industry heavyweights bring a wealth of expertise and connections, offering participants unparalleled opportunities for networking and professional growth. While some observers have pointed out the challenges of translating hackathon innovations into real-world applications, the organizers have taken proactive steps to address this concern. By involving industry partners and offering ongoing support services to winners, the event aims to create a bridge between innovative ideas and practical implementation. This approach not only enhances the long-term impact of the hackathon but also provides a valuable model for future events in the Web3 space. The "DMCC x Bybit Web3 Unleashed" hackathon represents a significant step forward in the global effort to harness the power of Web3 technologies for societal benefit. By focusing on real-world problem-solving and bringing together a diverse array of stakeholders, the event has the potential to catalyze meaningful innovation in the Web3 space. As the Web3 ecosystem continues to evolve and mature, events like these will likely play an increasingly important role in shaping its trajectory. The success of this hackathon could serve as a model for future collaborative efforts aimed at leveraging emerging technologies to address pressing global challenges. The organizers' commitment to fostering ongoing development and implementation of winning projects demonstrates a forward-thinking approach to innovation. This holistic strategy not only enhances the value of the hackathon for participants but also increases the likelihood of generating lasting, impactful solutions to real-world problems. As the Web3 industry continues to grow and evolve, events like the "DMCC x Bybit Web3 Unleashed" hackathon will be crucial in driving innovation, fostering collaboration, and ultimately shaping the future of technology. With its focus on real-world applications and strong industry support, this event stands as a beacon of progress in the ongoing development of the Web3 ecosystem. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

Global Tech Talents to Pitch Live in Dubai at 'DMCC x Bybit Web3 Unleashed' Event

Global Tech Talents to představí živě v Dubaji na události 'DMCC x Bybit Web3 Unleashed'

Talentos tecnológicos globales se presentarán en vivo en Dubái en el evento 'DMCC x Bybit Web3 Unleashed'

Global Tech Talents esittelee livenä Dubaissa DMCC x Bybit Web3 Unleashed -tapahtumassa

世界的な技術系人材がドバイの「DMCC x Bybit Web3 Unleashed」イベントでライブプレゼンテーション

Жаһандық технологиялық таланттар Дубайда «DMCC x Bybit Web3 Unleashed» іс-шарасында тікелей эфирге шығады

Wereldwijde techtalenten pitchen live in Dubai tijdens het evenement 'DMCC x Bybit Web3 Unleashed'

Global Tech Talentos Dubai llaqtapi kawsaqlla rimanankupaq 'DMCC x Bybit Web3 Unleashed' Eventopi

Global Tech Talents Kuanzisha Moja kwa Moja huko Dubai kwenye Tukio la 'DMCC x Bybit Web3 Unleashed'

เหล่าบุคลากรด้านเทคโนโลยีระดับโลกเตรียมนำเสนอผลงานสดในงาน 'DMCC x Bybit Web3 Unleashed' ที่ดูไบ

Titalenta ta Thekinoloji ta Misava Hinkwayo ti ta Pitch Live eDubai eka 'DMCC x Bybit Web3 Unleashed' Event

گلوبل ٹیک ٹیلنٹ دبئی میں 'DMCC x Bybit Web3 Unleashed' ایونٹ میں لائیو پیش کریں گے۔

Global Tech Talents sẽ trình bày trực tiếp tại Dubai tại sự kiện 'DMCC x Bybit Web3 Unleashed'

Uncovering Gender Bias in Talent Shows: Insights from The Voice

Author:
(1) Anuar Assamidanov, Department of Economics, Claremont Graduate University, 150 E 10th St, Claremont, CA 91711. (Email: anuar.assamidanov@cgu.edu). Table of Links Abstract Background Data Methodology Results Discussion and Conclusion, and References A Appendix Tables and Figures A Appendix Tables and Figures Notes: Table A1 presents a difference in differences estimate of gender bias using regression of Equation 1. This table reports the coefficient on the interaction of Male Artist and Male Coach from the regression of Choice on indicators for coach gender, artist gender, and the interaction term. The reported coefficients are for ”own-gender coach” using data subsets by country indicated in columns. Each specification includes coach and country fixed effects, the order of the performance fixed effects, genre-fixed effects, the number of males relative to females in the team, the failure rate of the coach for female artists, and the failure rate of the coach for male artists. Standard errors are clustered by coach. ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01 Notes: Table A2 presents a difference in differences estimate of gender bias using regression of Equation 1. This table reports the coefficient on the interaction of Male Artist and Male Coach from the regression of Choice on indicators for coach gender, artist gender, and the interaction term. The reported coefficients are for ”own-gender coach” using data subsets by gender composition in the team indicated in columns. X < −2 means that difference in the number of women and men in the team is 3 or higher. Similarly, X > 3 means that difference in the number of men and women is 4 or higher. Each specification includes coach and country fixed effects, the order of the performance fixed effects, genre-fixed effects, the failure rate of the coach for female artists, and the failure rate of the coach for male artists. Standard errors are clustered by coach. ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01 This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for the failure rate of coaches for male artists. This is the rate at which a coach wanted an artist of a particular gender on their team, and the artist did not choose the coach. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the failure rate of coaches for male artists. Standard errors clustered by coach. This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for the failure rate of coaches for female artists. This is the rate at which a coach wanted an artist of a particular gender on their team, and the artist did not choose the coach. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the failure rate of coaches for female artists. Standard errors clustered by coach. This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for each audition episode. Each 10th order of ten performances aggregates into the episodes in the same order. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the grouped order of performance. Standard errors clustered by coach. This paper is available on arxiv under CC 4.0 license. Author: (1) Anuar Assamidanov, Department of Economics, Claremont Graduate University, 150 E 10th St, Claremont, CA 91711. (Email: anuar.assamidanov@cgu.edu). Author: Author: (1) Anuar Assamidanov, Department of Economics, Claremont Graduate University, 150 E 10th St, Claremont, CA 91711. (Email: anuar.assamidanov@cgu.edu). Table of Links Abstract Abstract Background Background Data Data Methodology Methodology Results Results Discussion and Conclusion, and References Discussion and Conclusion, and References A Appendix Tables and Figures A Appendix Tables and Figures A Appendix Tables and Figures Notes: Table A1 presents a difference in differences estimate of gender bias using regression of Equation 1. This table reports the coefficient on the interaction of Male Artist and Male Coach from the regression of Choice on indicators for coach gender, artist gender, and the interaction term. The reported coefficients are for ”own-gender coach” using data subsets by country indicated in columns. Each specification includes coach and country fixed effects, the order of the performance fixed effects, genre-fixed effects, the number of males relative to females in the team, the failure rate of the coach for female artists, and the failure rate of the coach for male artists. Standard errors are clustered by coach. ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01 Notes: Table A2 presents a difference in differences estimate of gender bias using regression of Equation 1. This table reports the coefficient on the interaction of Male Artist and Male Coach from the regression of Choice on indicators for coach gender, artist gender, and the interaction term. The reported coefficients are for ”own-gender coach” using data subsets by gender composition in the team indicated in columns. X < −2 means that difference in the number of women and men in the team is 3 or higher. Similarly, X > 3 means that difference in the number of men and women is 4 or higher. Each specification includes coach and country fixed effects, the order of the performance fixed effects, genre-fixed effects, the failure rate of the coach for female artists, and the failure rate of the coach for male artists. Standard errors are clustered by coach. ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01 This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for the failure rate of coaches for male artists. This is the rate at which a coach wanted an artist of a particular gender on their team, and the artist did not choose the coach. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the failure rate of coaches for male artists. Standard errors clustered by coach. This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for the failure rate of coaches for female artists. This is the rate at which a coach wanted an artist of a particular gender on their team, and the artist did not choose the coach. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the failure rate of coaches for female artists. Standard errors clustered by coach. This figure summarizes the results from the causal forest by approach in Athey and Wager (2019), where each estimate shown represents the effect of own-gender and opposite-gender interactions on selecting the artists in the case controlling for the gender of the coach and coach fixed effects. From left to right, the outcome of interest is a set of indicators for each audition episode. Each 10th order of ten performances aggregates into the episodes in the same order. This result effectively yields the estimates of own and opposite gender bias in selections that are specific to variation by the grouped order of performance. Standard errors clustered by coach. This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv

Exploring Own-Gender Bias in Talent Selections

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