The 2024 Bilderberg Conference was held between May 30–June 2, 2024 in Madrid, Spain at the Eurostars Suites Mirasierra hotel. The 2024 meeting was the 70th edition of the event. A Bilderberg Group press release stated that there were 131 participants from around 25 countries. Established in 1954 by Prince Bernhard of the Netherlands, Bilderberg conferences (or meetings) are an annual private gathering of the European and North American political and business elite. Events are attended by between 120 and 150 people each year invited by the Bilderberg Group's steering committee; including prominent politicians, CEOs, national security experts, academics and journalists. Several US presidents have attended the meetings before winning a presidential election. These politicians include Bill Clinton and Barack Obama. Bilderberg conferences operate under the Chatham House Rule, meaning that participants are sworn to secrecy and cannot disclose the identity or affiliation of any particular speaker. == Agenda == The key topics for discussion were announced on the Bilderberg website shortly before the meeting. These topics included: == Participants == A list of 131 participants was published on the Bilderberg website. This list may not be complete, as a source connected to the Bilderberg group told The Daily Telegraph in 2013 that some attendees do not have their names publicized. King Felipe VI of Spain was reported to have attended the meeting despite his name not being on the list.
Tradeshift
Tradeshift is a cloud based business network and platform for purchase-to-pay automation, supply chain payments, marketplaces, virtual cards and supply chain financing. Its 2018 round of funding, led by Goldman Sachs, raised US$250 million at a valuation of $1.1 billion, giving the company unicorn status. Tradeshift is headquartered in San Francisco, California and has offices in London, Copenhagen, Bucharest and Kuala Lumpur. Tradeshift has reprocessed over $1 trillion USD through transactions on its network. == History == Tradeshift was founded in 2010 by Christian Lanng, Mikkel Hippe Brun, and Gert Sylvest. Inspiration for Tradeshift came after they created the world's first large scale peer-to-peer infrastructure for an e-business called NemHandel. The founders also had leading roles (Governing board member, Technical Director) in the European Commission project PEPPOL inside the European Union. In 2010, the Tradeshift platform launched in May in Copenhagen. Tradeshift won the European Startup Awards in the category of "Best Business or Enterprise Startup." In 2011, Tradeshift made its app marketplace available. In 2012, Tradeshift moved their headquarters from Copenhagen to San Francisco. In 2013, Tradeshift opened an R&D center in Suzhou, China. Tradeshift opened an additional office in London. And LATAM e-invoicing capabilities were added through partnership with Invoiceware. In 2014, Tradeshift expanded with offices in Tokyo, Paris, and Munich. The EU Commission officially approved the Universal Business Language (UBL) data format – a format Tradeshift supports – as eligible for referencing in tenders from public administrations. In 2015, Tradeshift won the Circulars "Digital Disruptor" Award at the WEF conference in Davos, Switzerland. Tradeshift also acquired product information management company Merchantry, and launched e-procurement and supplier risk management solutions. In 2016, Tradeshift acquired Hyper Travel and secured a $75 million series-D round funding. In 2017, Tradeshift acquired IBX Business Network and launches Tradeshift Ada. In 2018, Tradeshift secured a $250 million series-E round funding. and launched Blockchain Payments, the latter as part of Tradeshift Pay. In December 2018 Tradeshift acquired Babelway, an online B2B integration platform. The acquisition added three new office locations to Tradeshift (Salt Lake City, Louvain-la-neuve, Belgium, Cairo Egypt). In Q3 2018, Tradeshift reported year-over-year revenue growth of 400%, new bookings growth of 284%, and gross merchandise volume (GMV) growth of 262%. New total contract value also grew by US$47 million. Additionally, it added 27 new customers including Hertz, Shiseido, ECU and multiple Fortune 500 companies. In July 2023, HSBC and Tradeshift announced an agreement to launch a new, jointly owned business focused on the development of embedded finance solutions and financial services apps. As part of the agreement, HSBC made a $35 million investment into Tradeshift and joined its board. The agreement was part of a funding round which is expected to raise a minimum of $70 million from HSBC and other investors. The new joint venture will allow HSBC and Tradeshift to deploy a range of digital solutions across Tradeshift and other platforms. This includes payment and fintech services embedded into trade, e-commerce and marketplace experiences. In September 2023, CEO Lanng was fired for "gross misconduct on multiple grounds," including "allegations of sexual assault and harassment." Tradeshift was alleged to have fired his accuser after she complained to the company's human resources department, its co-founders and members of its board of directors about his abuse. == Financials == The company's valuation as of May 2018 was $1.1 billion. Tradeshift is now considered a unicorn, and, according to Bloomberg, will not need any further funding. Jan 14, 2020, Tradeshift announced that they had raised $240 million in Series F finance. == Acquisitions == In 2015, Tradeshift acquired product information management company Merchantry. Merchantry is a retail product information management (PIM) software for multi-vendor ecommerce retailers. In 2016, Tradeshift acquired Hyper Travel. Hyper Travel is a travel management service that allows customers to access travel agents via its native messaging apps, SMS, and email. In 2017, Tradeshift acquired IBX Group. In 2018, Tradeshift acquired Babelway, an online B2B integration platform.
Amazon Kinesis
Amazon Kinesis is a family of services provided by Amazon Web Services (AWS) for processing and analyzing real-time streaming data at a large scale. Launched in November 2013, it offers developers the ability to build applications that can consume and process data from multiple sources simultaneously. Kinesis supports multiple use cases, including real-time analytics, log and event data collection, and real-time processing of data generated by IoT devices. == History == Amazon Kinesis was launched by Amazon Web Services (AWS) in November 2013 as a managed service for processing and analyzing real-time streaming data at a large scale. The service was introduced to address the growing need for businesses to process and analyze data as it was generated, rather than in batches, allowing for real-time insights and decision-making. Since its launch, the Amazon Kinesis family of services has expanded to include four main components: Kinesis Data Streams, Kinesis Data Firehose, Kinesis Data Analytics, and Kinesis Video Streams. Each of these components serves a specific purpose in the processing and analysis of real-time streaming data. In August 2015, AWS announced the availability of Kinesis Data Firehose, a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, and Amazon Elasticsearch. A year later in August 2016, AWS launched Kinesis Data Analytics, enabling customers to analyze streaming data in real time using standard SQL queries. AWS introduced Kinesis Video Streams, a fully managed service for securely capturing, processing, and storing video streams for analytics and machine learning applications, was introduced by AWS in November 2017. == Components == Amazon Kinesis is composed of four main services: Kinesis Data Streams, Kinesis Data Firehose, Kinesis Data Analytics, and Kinesis Video Streams. === Kinesis Data Streams === Kinesis Data Streams is a scalable and durable real-time data streaming service that captures and processes gigabytes of data per second from multiple sources. It enables the storage and processing of data in real time, making it useful for applications that require immediate insights, such as monitoring and alerting. === Kinesis Data Firehose === Kinesis Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon Elasticsearch, and AWS-partner data stores. With Data Firehose, users can configure and scale data delivery without manual intervention. === Kinesis Data Analytics === Kinesis Data Analytics enables the analysis of streaming data in real time using standard SQL or Apache Flink. === Kinesis Video Streams === Kinesis Video Streams is a fully managed service for securely capturing, processing, and storing video streams for analytics and machine learning. It supports multiple video codecs and streaming protocols, making it suitable for various use cases, such as security and surveillance, video-enabled IoT devices, and live event broadcasting. == Integration == Amazon Kinesis can be easily integrated with other AWS services, such as AWS Lambda, Amazon S3, Amazon Redshift, and Amazon OpenSearch. This integration enables developers to build end-to-end streaming data processing applications, taking advantage of the extensive AWS ecosystem. == Use cases == Some common use cases for Amazon Kinesis include: Real-time analytics: Analyzing streaming data in real time to provide immediate insights and make data-driven decisions. Log and event data collection: Collecting, processing, and analyzing log and event data generated by applications, infrastructure, and devices. IoT data processing: Processing and analyzing large volumes of data generated by IoT devices in real time. Machine learning: Ingesting and processing video streams for machine learning applications, such as object recognition, facial recognition, and sentiment analysis. == Pricing == Amazon Kinesis follows a pay-as-you-go pricing model, with costs depending on the chosen service, data volume, and processing power required. AWS provides a free tier for Kinesis Data Streams and Kinesis Data Firehose, allowing users to get started with the services at no cost.
Test data
Test data are sets of inputs or information used to verify the correctness, performance, and reliability of software systems. Test data encompass various types, such as positive and negative scenarios, edge cases, and realistic user scenarios, and aims to exercise different aspects of the software to uncover bugs and validate its behavior. Test data is also used in regression testing to verify that new code changes or enhancements do not introduce unintended side effects or break existing functionalities. == Background == Test data may be used to verify that a given set of inputs to a function produces an expected result. Alternatively, data can be used to challenge the program's ability to handle unusual, extreme, exceptional, or unexpected inputs. Test data can be produced in a focused or systematic manner, as is typically the case in domain testing, or through less focused approaches, such as high-volume randomized automated tests. Test data can be generated by the tester or by a program or function that assists the tester. It can be recorded for reuse or used only once. Test data may be created manually, using data generation tools (often based on randomness), or retrieved from an existing production environment. The data set may consist of synthetic (fake) data, but ideally, it should include representative (real) data. == Limitations == Due to privacy regulations such as GDPR, PCI, and the HIPAA, the use of privacy-sensitive personal data for testing is restricted. However, anonymized (and preferably subsetted) production data may be used as representative data for testing and development. Programmers may also choose to generate synthetic data as an alternative to using real or anonymized data. While synthetic data can offer significant advantages, such as enhanced privacy and flexibility, it also comes with limitations. For instance, generating synthetic data that accurately reflects real-world complexity can be challenging. There is also a risk of synthetic data not fully capturing the nuances of real data, potentially leading to gaps in test coverage. == Domain testing == Domain testing is a set of techniques focusing on test data. This includes identifying critical inputs, values at the boundaries between equivalence classes, and combinations of inputs that drive the system toward specific outputs. Domain testing helps ensure that various scenarios are effectively tested, including edge cases and unusual conditions.
List of C software and tools
This is a list of software and programming tools for the C programming language, including libraries, debuggers, compilers, integrated development environments (IDEs), and other related development tools and utilities. == Libraries and tools == Adns — asynchronous DNS resolver library Advanced Linux Sound Architecture — API for sound card device drivers Allegro — cross-platform software library for video game development Apache Portable Runtime — Apache web server tool set of APIs that map to the underlying operating system Argon2 — memory-hard password hashing library Berkeley DB — embedded database software library for key/value data Binary File Descriptor library — binary file manipulation library in the GNU toolchain Boehm garbage collector – conservative garbage collector Borland Graphics Interface — graphics library for Borland compilers BSAFE — FIPS 140-2 validated cryptography library Chipmunk — 2D real-time rigid body physics engine C POSIX library — specification of a C standard library for POSIX systems C standard library – standard library for the C programming language Cairo – vector graphics library API for software developers CFD General Notation System (CGNS) — data format and library for computational fluid dynamics cJSON — lightweight JSON parser CLIPS — public-domain software tool for building expert systems Core Audio — low-level API for dealing with sound in Apple's macOS and iOS operating systems Core Foundation — API for macOS and iOS and other Apple operating systems Core Image — GPU accelerated image processing technology for Apple operating systems with Quartz graphics rendering layer. Core Text — text layout and font rendering API for macOS and iOS. Cryptlib — portable cryptography library cURL / libcurl — CLI app for uploading and downloading individual files, such as a URL from a web server over HTTP. DevIL — cross-platform image library for loading and converting file formats DirectFB — graphics acceleration and input device handling library Dld — dynamic loading library Expat — stream-oriented XML 1.0 parser library, written in C99. FFmpeg — multimedia framework for audio/video processing Fontconfig — font customization and configuration library FreeTDS — database library for Sybase and Microsoft SQL Server FreeType — render text onto bitmaps with a font rasterization engine GD Graphics Library — image creation and manipulation library GDK — graphics abstraction layer for GTK GEGL — graph-based image processing framework GIO — I/O and virtual file system library in GLib GLib — utility library providing data structures, event loops, and portability functions. glibc — GNU implementation of the C standard library GLFW — library for OpenGL contexts, windows, and input device handling GNet — networking library for GLib GNU Libtool — Library management tool GNU portability library — collection of portability routines for GNU software GNU Portable Threads — POSIX/ANSI-C based user space thread library for UNIX for scheduling multithreading GNU Readline — command-line editing library GnuTLS — secure communications (TLS/SSL) library GObject — object system library for GNOME GTK — widget toolkit for creating graphical user interfaces GTK Scene Graph Kit (GSK) — scene graph and rendering toolkit for GTK HDF — file format and library for managing large datasets Integrated Performance Primitives — Intel library of optimized multimedia and data processing routines IUP — portable GUI toolkit J2K-Codec — JPEG 2000 image codec JasPer — reference implementation of the codec specified in the JPEG-2000 Part-1 standard LDAP API — API for interacting with Lightweight Directory Access Protocol LZO — lossless compression library Liba52 — decoder for A/52 (AC-3) audio streams libarchive — reading and writing various archive and compression formats Libart — 2D graphics library Libavcodec — codec library from FFmpeg Libavdevice — library for handling multimedia devices Libavfilter — audio and video filter library Libavformat — library for muxing and demuxing multimedia Libpcap — packet capture library Libdca — decoder for DTS audio Libdvdcss — access to encrypted DVD-Video discs libevent — asynchronous event notification callbacks libffi — foreign function interface libfuse — userspace filesystem Libgegl — programming interface to GEGL image processing libgcrypt — cryptography Libgimp — plug-in development library for GIMP Libhybris — compatibility layer for running Android libraries on Linux Libinput — input device library for Wayland and X.Org libjpeg — JPEG image library libLAS — reading and writing geospatial data encoded in the ASPRS laser (LAS) file format libmicrohttpd — small C library for embedding HTTP server functionality Libmpcodecs — media player codec library from MPlayer Libmpdemux — demultiplexing library from MPlayer libpng — PNG image format Libpostproc — video post-processing library from FFmpeg libpq — PostgreSQL client LibreSSL — fork of OpenSSL for TLS Librsb — parallel library for sparse matrix computations Librsvg — SVG rendering library libsndfile — reading and writing audio files libsodium — easy-to-use cryptography library Libswscale — image scaling and colorspace conversion library LibTIFF — TIFF image handling library Libusb — USB device access library Libuv — asynchronous I/O and event loop library LibVLC — media player engine from VLC LibVNCServer — implementation of the VNC server protocol Libvpx — VP8 and VP9 video codec library Libwww — early World Wide Web protocol library from W3C libxml2 — XML parsing Libxslt — XSLT library for the GNOME Project libzip — ZIP archives Lightning Memory-Mapped Database — fast key–value database engine LittleCMS — open-source color management system LZ4 — fast lossless compression algorithm LZFSE — compression library developed by Apple MatrixSSL — lightweight TLS implementation Mbed TLS — portable cryptography and TLS library MediaLib — Sun Microsystems library for multimedia processing Mesa — OpenGL and Vulkan graphics library Microwindows — small windowing system for embedded devices Ming — library for generating SWF (Flash) files Mongoose — embedded web server and networking library Mpg123 — MP3 audio decoding library MPIR — multiple-precision arithmetic library MsQuic — Microsoft implementation of the QUIC transport protocol MuJoCo — physics engine for robotics and control Mustache — logic-less templating library Ncurses — terminal control library Nettle — low-level cryptography library Newt — text-based user interface library Netpbm — graphics conversion and processing library Nghttp2 — implementation of the HTTP/2 protocol Oniguruma — regular expression library Open Asset Import Library — library to import/export 3D model formats OpenCL — parallel computing API/library OpenCV — computer vision OpenGL — API for rendering 2D and 3D vector graphics OpenGL Utility Library — OpenGL utility functions OpenJPEG — JPEG 2000 image codec OpenSSL — SSL and TLS protocols and cryptography library Pango — layout engine library which works with the HarfBuzz shaping engine for displaying multi-language text perf (Linux) — performance analyzing tool PCRE — regular expression library PROJ — library for map projections and coordinate transforms Quartz 2D — 2D graphics rendering API for macOS and iOS platforms, part of the Core Graphics framework. Raylib — simple library for games and multimedia Redland RDF Application Framework — RDF data storage library S2n-tls — TLS implementation from AWS Setcontext — context switching library functions SDL — Simple DirectMedia Layer systemd — system and service manager libraries for Linux Tk — GUI widgets for building graphical user interfaces VDPAU — video decoding acceleration API Vorbis — audio compression codec library VTD-XML — high-performance XML parser Wimlib — library for handling Windows Imaging Format disk images Windows.h — base Windows API header file WolfSSH — lightweight SSH library WolfSSL — lightweight SSL/TLS library X Toolkit Intrinsics — toolkit library for the X Window System x264 — H.264 video codec library XCB — C binding for the X Window System protocol Xft — font rendering library using FreeType Xlib — low-level X Window System API XMDF — eXtensible Model Data Format for scientific data XMLStarlet — XML command-line toolkit zlib — data compression Zopfli — data compression library that performs deflate, gzip and zlib data encoding. Zstd — fast data compression library == Integrated development environments == Anjuta — GNOME IDE CLion — cross-platform commercial IDE from JetBrains Code::Blocks — cross-platform open-source IDE CodeLite — open-source IDE Dev-C++ Eclipse CDT Geany — text editor with IDE features KDevelop — KDE IDE NetBeans Qt Creator SlickEdit Visual Studio Xcode === Online IDEs === CodeSandbox — online IDE primarily for web development with some C support via containers GitHub Codespaces — cloud-based online IDE developed by GitHub Google Cloud Shell — browser-based shell and editor that can comp
Continuous Function Chart
A Continuous Function Chart (CFC) is a graphic editor that can be used in conjunction with the STEP 7 software package or with other tools, such as CODESYS. It is used to create the entire software structure of the CPU from ready-made blocks. When working with the editor, you place blocks on function charts, assign parameters to them, and interconnect them. Interconnecting means, for example, that values are transferred from one output to one or more inputs during communication between the blocks. Continuous function charts are basically used for controlling continuous processes, where all the logic is executed and outputs are calculated in each PLC scan. Whereas in SFC, execution will be sequential as done is batch processes.
Message queuing service
A message queueing service is a message-oriented middleware or MOM deployed in a compute cloud using software as a service model. Service subscribers access queues and or topics to exchange data using point-to-point or publish and subscribe patterns. It's important to differentiate between event-driven and message-driven (aka queue driven) services: Event-driven services (e.g. AWS SNS) are decoupled from their consumers. Whereas queue / message driven services (e.g. AWS SQS) are coupled with their consumers. Message queues can be a good buffer to handle spiky workloads but they have a finite capacity. According to Gregor Hohpe, message queues require proper mechanisms (aka flow controls) to avoid filling the queue beyond its manageable capacity and to keep the system stable. == Ordering Guarantees in Message Queues == Amazon SQS FIFO and Azure Service Bus sessions are queue-based messaging systems that provide ordering guarantees within a message group or session attempt but do not necessarily guarantee ordered delivery in cases of retries or failures. In SQS FIFO, messages in the same message group are processed in order, with subsequent messages held until the preceding message is successfully processed or moved to the dead-letter queue (DLQ). Once a message is placed in the DLQ, it is no longer retried, creating a gap in the sequence. However, the remaining messages continue to be delivered in order. Azure Service Bus sessions function similarly by maintaining ordering within a session, provided a single consumer processes messages sequentially. The implementation differs from SQS FIFO but follows the same fundamental ordering principle. In contrast, Apache Kafka is a distributed log-based messaging system that guarantees ordering within individual partitions rather than across the entire topic. Unlike queue-based systems, Kafka retains messages in a durable, append-only log, allowing multiple consumers to read at different offsets. Kafka uses manual offset management, giving consumers control over retries and failure handling. If a consumer fails to process a message, it can delay committing the offset, preventing further progress in that partition while other partitions remain unaffected. This partition-based design enables fault isolation and parallel processing while allowing ordering to be maintained within partitions, depending on consumer handling. == Vendors == Apache Kafka Apache Kafka is a distributed system consisting of servers that store and forward messages between producer client and consumer applications. IBM MQ IBM MQ offers a managed service that can be used on IBM Cloud and Amazon Web Services. Microsoft Azure Service Bus Service Bus offers queues, topics & subscriptions, and rules/actions in order to support publish-subscribe, temporal decoupling, and load balancing scenarios. Azure Service Bus is built on AMQP allowing any existing AMQP 1.0 client stack to interact with Service Bus directly or via existing .Net, Java, Node, and Python clients. Standard and Premium tiers allow for pay as you go or isolated resources at massive scale. Oracle Messaging Cloud Service This service provides a messaging solution for applications for asynchronous communication and is influenced by the Java Message Service (JMS) API specification. Any application platform that understands HTTP can also use Oracle Messaging Cloud Service through the REST interface. For Java applications, Oracle Messaging Cloud Service provides a Java library that implements and extends the JMS 1.1 interface. The Java library implements the JMS API by acting as a client of the REST API. Amazon Simple Queue Service Supports messages natively up to 256K, or up to 2GB by transmitting payload via S3. Highly scalable, durable and resilient. Provides loose-FIFO and 'at least once' delivery in order to provide massive scale. Supports REST API and optional Java Message Service client. Low latency. Utilizes Amazon Web Services. IronMQ Supports messages up to 64k; guarantees order; guarantees once only delivery; no delays retrieving messages. Supports REST API and beanstalkd open source protocol. Runs on multiple clouds including AWS and Rackspace. Scaling must be managed by user. RabbitMQ RabbitMQ is a reliable and mature messaging and streaming broker, which is easy to deploy on cloud environments, on-premises, and on your local machine. Supports AMQP, STOMP, MQTT StormMQ Open platform supports messages up to 50Mb. Uses AMQP to avoid vendor lock-in and provide language neutrality. Locate-It Option allows customers to audit the location of their data at all times and satisfy data protection principles. AnypointMQ An enterprise multi-tenant, cloud messaging service that performs advanced asynchronous messaging scenarios between applications. Anypoint MQ is fully integrated with Anypoint Platform, offering role based access control, client application management, and connectors.