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IDM

Intelligent dance music (IDM) is a form of electronic music that emerged in the early , characterized by intricate rhythms, abstract sound manipulation, unconventional structures, and a emphasis on cerebral listening experiences over dancefloor functionality. The genre draws from influences like , , and experimental , often featuring processed beats, ambient melodies, and unusual time signatures that prioritize innovation and close attention from listeners. The term "intelligent dance music" was popularized by the British label Warp Records through its 1992 compilation album Artificial Intelligence, which showcased artists producing non-dance-oriented electronic works amid the era's rave culture dominance. Pioneering figures include Aphex Twin (Richard D. James), Autechre, and μ-Ziq, whose albums emphasized sonic experimentation and algorithmic composition techniques, setting IDM apart as a "braindance" alternative— a term Aphex Twin preferred to avoid implications of intellectual superiority over other electronic styles. Other influential acts, such as Boards of Canada and The Black Dog, contributed to IDM's evolution by blending nostalgic samples, glitch elements, and atmospheric textures, influencing subsequent subgenres like drill 'n' bass and microsound. Despite its innovations, IDM has faced criticism for the term's perceived , suggesting that mainstream lacks sophistication, a view that has led some artists and critics to reject the label altogether. The genre's legacy endures in underground electronic scenes, with ongoing releases rewarding dedicated audiophiles through dense, rewarding productions that challenge conventional notions of and .

Technology and Computing

Identity Management

Identity management (IDM) encompasses the policies, procedures, and technologies organizations employ to create, maintain, and secure digital identities for users, devices, and applications within IT environments. This process ensures that entities are verified and granted appropriate to resources while minimizing risks such as unauthorized entry or breaches. typically forms the foundational layer of broader (IAM) frameworks, emphasizing the full lifecycle of identities—from initial provisioning during to de-provisioning upon termination—distinct from but complementary to access authorization mechanisms. Core components of IDM include identity provisioning, which automates the creation and synchronization of user accounts across systems; , verifying user identities via methods like passwords, , or ; and identity governance, which enforces compliance with regulations such as GDPR or through auditing and role-based access reviews. Effective IDM reduces administrative overhead by centralizing identity data in directories like LDAP, established as an IETF standard in 1993, and integrates with modern directories such as , deployed by in 1999 for Windows 2000. Systems must handle scalability for enterprises, where a 2023 Gartner report noted that 75% of organizations experienced identity-related incidents due to poor practices. Key standards underpin interoperable IDM implementations. SAML 2.0, ratified by OASIS in 2005, enables secure identity federation across domains by exchanging authentication assertions in XML format, widely used for single sign-on (SSO) in enterprise settings. OAuth 2.0, published as RFC 6749 in 2012 by the IETF, facilitates delegated authorization, allowing third-party applications to access resources without sharing credentials, though it requires extensions like OpenID Connect (OIDC) for robust authentication. OIDC, built atop OAuth 2.0 and standardized in 2014, adds identity layers such as ID tokens for verifiable claims, supporting modern web and mobile ecosystems. These protocols address historical silos in identity systems, which originated in the 1980s with mainframe user registries and evolved through the 1990s directory services boom amid internet growth. In contemporary deployments, IDM adapts to cloud-native architectures and zero-trust models, incorporating just-in-time provisioning via , an IETF standard from 2011 that automates user lifecycle events across applications. Challenges persist, including proliferation—where unmanaged identities evade oversight—and the surge in non-human identities like , projected to outnumber human ones 5:1 by 2025 per industry analyses. Robust IDM mitigates these by enforcing least-privilege principles, with tools from vendors like and reporting up to 99% reduction in breach risks through automated governance.

Internet Download Manager

Internet Download Manager (IDM) is a download management application developed by Tonec Inc. for Microsoft Windows operating systems. It functions by intercepting download links from web browsers, segmenting files into multiple parts for parallel downloading, and reassembling them to achieve higher speeds and reliability compared to native browser downloaders. The software supports resuming interrupted downloads, scheduling, and categorization, making it popular among users handling large files or unstable connections. Tonec Inc., based in the with operations linked to entities like Tonec FZE, initiated development of IDM in the late , with the software's dating to 1999. Initial public releases appeared around 2001, evolving through regular updates to address , video streaming support, and enhancements. As of October 2025, the stable version is 6.42 Build 51, released on October 15, which includes fixes for video stream downloads and integration issues. IDM offers a 30-day free trial, after which a paid is required for full functionality without nag screens, priced at approximately $25 for a single-user lifetime . Key features include dynamic file segmentation, which divides downloads into up to 32 parts for concurrent retrieval, potentially increasing speeds by up to 8 times over single-threaded methods, though actual gains depend on server limits and network conditions. It integrates via extensions with browsers such as , Mozilla Firefox, and , automatically capturing and . Additional capabilities encompass recovery from partial failures, a built-in download scheduler, , and a video grabber for extracting streams from sites like . Users can organize files into custom categories and set site-specific download rules. IDM has faced challenges with browser updates, notably Chrome's Manifest V3 policy in , which initially disabled its extension alongside ad blockers, prompting workarounds like helper applications from the developer. Despite this, it remains widely used for its reliability in batch and high-volume downloading, though alternatives exist for open-source preferences or cross-platform needs. The software's association with has drawn scrutiny in some contexts, but its core utility stems from technical optimizations rather than endorsement of illicit use.

Integrated Device Manufacturer

An integrated device manufacturer (IDM) is a company that internally handles the , fabrication, testing, and packaging of integrated circuits (ICs), while also selling the end products under its own brand. This vertically integrated approach contrasts with fabless firms, which outsource , and pure-play foundries, which produce chips solely for external clients. IDMs maintain control over proprietary processes to optimize performance, yield, and innovation, though this requires substantial capital expenditures on fabrication facilities (fabs), often exceeding $10 billion per advanced node plant. The IDM model emerged in the mid-20th century as firms like and developed in-house capabilities to produce , starting with early innovations such as Jack Kilby's 1958 integrated circuit at . By the and , IDMs dominated the industry, leveraging owned fabs for competitive advantages in scaling production of memory, logic, and analog chips. However, escalating costs of sub-10nm process nodes—driven by and other technologies—prompted shifts; for instance, faced delays in its 10nm rollout from 2016 to 2019, highlighting risks of self-reliance amid rapid technological evolution. Prominent IDMs include , which as of 2023 held significant market share in x86 processors with in-house fabs in the , , and ; , producing , , and logic chips while also offering services; , focused on analog and embedded processing with fabs in the and ; , specializing in power s; and for memory. These firms accounted for a substantial portion of global revenue, with and vying for leadership in 2022 sales exceeding $50 billion each. IDMs face pressures from the foundry-fabless ecosystem, where companies like fabricate for fabless designers such as , enabling specialization but introducing vulnerabilities exposed during the 2020-2022 . In response, hybrid strategies have proliferated; expanded its arm to serve external clients, while announced ambitions in 2021 via Intel Foundry Services to compete with . Despite these adaptations, IDMs retain strengths in closed-loop optimization, such as 's of memory and logic for mobile applications, supporting sectors like automotive, , and data centers.

Intelligent Driver Model

The Intelligent Driver Model (IDM) is a deterministic, time-continuous microscopic car-following model used in simulation to describe the longitudinal of vehicles in response to leading vehicles. Developed by Martin Treiber, Arne Hennecke, and Dirk Helbing at the , it was introduced in 2000 within a study on congested states, aiming to replicate empirical observations of breakdown and multiscale structures in jams through simplified yet realistic . The model balances two primary objectives: maintaining a desired while ensuring a safe dynamic distance to the vehicle ahead, thereby avoiding collisions and producing smooth profiles under varying conditions such as free flow, following, and braking. The core equation for the acceleration a_n(t) of vehicle n is given by
a_n(t) = a \left[ 1 - \left( \frac{v_n(t)}{v_0} \right)^\delta - \left( \frac{s_n^*(t)}{s_n(t)} \right)^2 \right],
where v_n(t) is the current speed, s_n(t) is the to the leading , and the desired s_n^*(t) = s_0 + \max\left( T v_n(t) + \frac{v_n(t) \Delta v_n(t)}{2 \sqrt{a b}}, 0 \right), with \Delta v_n(t) as the relative speed (speed of leader minus v_n). This formulation incorporates a free-road term $1 - (v/v_0)^\delta for approaching the desired speed v_0 with reduced at high speeds (controlled by exponent \delta), and an term -(s^*/s)^2 for spacing adjustment, which becomes dominant near the leader and ensures string stability by perturbations.
IDM employs six intuitive parameters, each corresponding to observable driving behaviors:
ParameterDescriptionTypical Value (Cars)Typical Value (Trucks)
v_0Desired free-flow speed120 km/h80 km/h
TDesired time headway1.5 s1.7 s
s_0Minimum net gap (e.g., vehicle length excluded)2 m2 m
aMaximum acceleration0.3–1.5 m/s² (calibration-dependent)0.3–1.0 m/s²
bComfortable (desired) braking deceleration3.0 m/s²2.0 m/s²
\deltaAcceleration exponent for smooth speed approach44
These parameters allow calibration to real-world data, such as from trajectory datasets, enabling differentiation between vehicle classes and avoidance of unrealistic behaviors like rear-end collisions when properly tuned. The model's advantages include its simplicity, computational efficiency for large-scale simulations, and ability to generate realistic phenomena like spontaneous traffic jams from small perturbations without stochastic elements, as validated against empirical data from sources like the NGSIM dataset. It has been integrated into software such as SUMO for microscopic traffic modeling and extended for applications in adaptive cruise control (ACC) design, autonomous vehicle platooning, and mixed human-automated traffic analysis. With over 3,400 citations by 2025, IDM remains the most referenced car-following model, outperforming alternatives in reproducing capacity drop at bottlenecks and wave propagation. Limitations include its assumption of perfect anticipation (no reaction delays in base form) and deterministic nature, which underrepresents human variability; extensions incorporate stochasticity, delays, or hybrid learning-based adjustments for improved fidelity to datasets like urban trajectory observations.

Music

Intelligent Dance Music

Intelligent dance music (IDM) is a genre of electronic music that originated in the early 1990s, primarily in the United Kingdom, as a reaction against the perceived simplicity of mainstream rave, house, and techno scenes. It emphasizes experimental sound design, complex rhythms, and abstract structures suited more for attentive listening than dancefloor utility, drawing influences from Detroit techno, Chicago house, and ambient music. The genre gained prominence through Warp Records' 1992 compilation Artificial Intelligence, which featured tracks from artists like Autechre, Aphex Twin (Richard D. James), LFO, and B12, positioning IDM as "electronic listening music" amid the post-rave shift toward home-based consumption. The term "" emerged around 1992–1993, with attributions varying between magazine's usage to describe cerebral electronic tracks and the creation of the IDM in the for discussing non-club-oriented . Warp's marketing of as music for the "intelligent" listener further solidified the label, though it was not coined by the label itself. By the mid-1990s, IDM had expanded via subsequent Warp releases and labels like Rephlex (founded by in 1991), fostering a scene that prioritized innovation over commercial dance trends. IDM's sonic hallmarks include intricate polyrhythms, glitch-like micro-edits, unconventional time signatures, and layered textures achieved through digital synthesis, granular processing, and sampling. Tracks often feature non-repetitive structures, ambient drones, and futuristic timbres, blending elements of , , and while avoiding predictable four-on-the-floor beats. This focus on compositional depth over physical groove led to its association with "braindance," a term preferred by some artists like to highlight its intellectual and playful ethos. Prominent artists include , whose 1992 album Selected Ambient Works 85-92 exemplified IDM's ambient-techno fusion; , known for algorithmic rhythms evolving into abstract noise on releases like (1995); and (Tom Jenkinson), who integrated jazz basslines with breakbeat complexity on (1997). Other key figures encompass with their nostalgic, analog-warm soundscapes on Music Has the Right to Children (1998), μ-Ziq's melodic experiments, and Plaid's textural IDM on Not for Threes (1997). These works, often released on or affiliated imprints, numbered in dozens by the late 1990s, with over 100 influential albums cataloged in genre retrospectives. The term IDM has faced criticism for its elitist connotations, implying that genres like hardcore techno or lack sophistication, a view artists like rejected by calling it marketing hype. Detractors argue it created artificial divisions in electronic music, with some preferring "" or avoiding labels altogether. Despite this, IDM's legacy persists in subgenres like (e.g., Oval's 1993 94diskont), wonky, and modern experimental , influencing producers through accessible software like , which emerged in 2001 and facilitated similar beat manipulation. Sales data from indicate sustained catalog revenue, with compilations exceeding 100,000 units by the 2000s.

Slang and Informal Usage

I Don't Mind

"IDM" serves as an for "I don't mind" in informal texting, , and platforms such as and , expressing neutrality, flexibility, or lack of preference regarding a proposed situation or . This usage conveys that the speaker has no strong objection or attachment to the outcome, often signaling agreeability without commitment. For instance, in response to a query like "Pizza or burgers for dinner?", a reply of "IDM" indicates openness to either option. The acronym emerged in the early 2000s alongside the proliferation of texting and early digital communication tools, paralleling other expressions like "" for "I don't care." It gained traction in casual online interactions where brevity is valued, particularly among younger users in English-speaking regions, though its exact regional origins remain undocumented in formal linguistic studies. Unlike more dismissive phrases, "IDM" typically carries a polite or accommodating tone, avoiding confrontation while permitting alternatives. Examples of "IDM" in context include:
  • Friend: "Want to watch the movie at 7 PM?" Response: "IDM, whatever works for you."
  • "Is it okay if I bring a guest?" Response: "IDM."
While versatile, "IDM" is context-dependent and may be misinterpreted in formal settings as curt; its informal nature limits applicability to professional discourse. Alternative phrasings like "either is fine" or "up to you" serve similar functions in expanded text.

Organizations and Businesses

Notable Organizations Using IDM

Major financial institutions such as , , and have adopted (IDM) systems to secure user access and comply with regulatory requirements, as evidenced by their membership in the Identity Management Institute, which promotes IDM best practices among enterprises. Similarly, (CIBC) and Insurance leverage IDM frameworks to manage employee and customer identities efficiently. In the technology sector, Cisco Systems employs IDM solutions to handle complex access controls across its global operations, integrating them with broader cybersecurity strategies. Consulting firm also implements IDM to safeguard client and internal systems, reflecting its commitment to advanced governance. company deployed Omada Identity in 2023 to automate lifecycle , reducing IT workload and enhancing with standards like GDPR. In healthcare, various hospital systems have integrated IDM for capabilities, minimizing access-related disruptions while enforcing role-based permissions. A leading U.S. provider collaborated with in the early 2020s to roll out a comprehensive IDM platform, resulting in streamlined processes and reduced administrative overhead for millions of users. These implementations highlight IDM's role in mitigating risks from insider threats and credential misuse in large-scale enterprises.

Other Uses

Miscellaneous Acronyms and Terms

In computing and cybersecurity, IDM commonly denotes Identity Management, a set of processes, tools, and policies for handling user identities, , and access controls within organizations to mitigate risks like unauthorized access. This usage emerged prominently in during the early 2000s, with systems designed to automate identity provisioning, across directories, and with regulations such as or GDPR. For instance, Novell's Identity Manager, launched in 2003, provided a framework for bidirectional identity between disparate systems like LDAP directories and databases, reducing administrative overhead by up to 70% in large deployments according to vendor benchmarks. Less frequently, IDM refers to niche technical terms such as Integrated Data Management in database systems, where it describes unified platforms for , , and , as implemented in tools from vendors like for handling petabyte-scale enterprise data since the mid-2010s. In biomedical contexts, IDM can stand for Infectious Dose for 50% Mortality, a metric used in and to quantify the of pathogens or toxins causing death in 50% of test subjects, derived from dose-response curves in controlled experiments. These applications highlight IDM's versatility beyond dominant usages, though they remain domain-specific and less prevalent in general discourse.

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