Home Blog

Can You Actually Hack a Radio Sign?


In 2017, a malicious actor exploited the alerts in Dallas’s emergency siren system and set off alarms for over 90 minutes. Most of these assaults can have an effect on gadgets that use radio frequency (RF) know-how, from sensible safety programs to plane. RF additionally performs a important function in lots of navy programs comparable to navigation, radar, and communication programs. Widespread DoD use instances embrace satellite tv for pc communication (SATCOM), radar, and tactical knowledge hyperlinks that assist coordinate troop actions, sign place details about a goal, or assist preserve communication between plane and drones. A current report indicated the DoD is prone to potential RF assault vectors, indicating the necessity to higher perceive and stop vulnerabilities.

On this RF 101 information, we discover among the fundamentals of radio frequency communication, delve into the generalities of protocols and machine interactions, talk about frequent RF instruments, and uncover methods malicious actors can assault programs. We summarize the fundamentals of RF know-how and the dangers related to it, and we talk about how the SEI helps to safe wi-fi communications.

RF Fundamentals

The electromagnetic spectrum covers your entire vary of electromagnetic waves from very lengthy radio waves to seen mild to very brief, high-energy radiation comparable to X-rays and gamma rays. The radio spectrum is a subset of the broader electromagnetic spectrum and ranges in frequency from 3 Hz to three,000 GHz. The flexibility of RF waves to propagate, or journey via completely different mediums, together with the vacuum of area, permits wi-fi communication with out the necessity for bodily connection. RF alerts are basic to trendy communication programs, which allow lots of immediately’s applied sciences together with tv, radio broadcasts, mobile communication, and Wi-Fi connections. Wi-fi RF communication additionally performs a significant function in area domains, comparable to satellite tv for pc communication to floor stations, which allow transmission of telemetry knowledge, GPS, and different alerts. The radio spectrum may be divided into standardized bands starting from extraordinarily low frequency (ELF) to tremendously excessive frequency (THF) as seen under.

figure1_06162025

Determine 1: The Electromagnetic Spectrum

figure2_06162025

Determine 2: Frequency Spectrum

What Are Protocols and RF Modules?

RF modules are small digital gadgets which might be used to transmit and obtain radio alerts between two gadgets which might be bodily separated. Transmitters are chargeable for transmitting radio waves that carry analog or digital info, and receivers obtain the radio waves and recuperate the data. That is the idea of a wi-fi communications channel, the open-space path via which info is transmitted through electromagnetic waves with out the usage of bodily connections comparable to wires or cables. The general sign is constructed of the service sign, a periodic waveform that conveys info through modulations that encode the analog or digital info. Modulation is the method of various a service sign to encode knowledge then demodulating that obtained sign to decode knowledge. Modulation methods decide how info is transmitted over radio waves, affecting the effectivity and high quality of communication.

figure3_06162025

Determine 3: Block Diagram of Digital Communication System

There are completely different ways in which the data may be modulated. Widespread analog modulations embrace amplitude modulation (AM) and frequency modulation (FM). AM modulates a better frequency service with a decrease frequency sign by adjusting the amplitude of the service sign. The frequency of the service is unaltered, however the amplitude varies always. FM modulates by making comparatively small changes to the frequency of the service. These two strategies characterize the sorts of RF alerts on the acquainted AM and FM radio bands. Widespread digital modulations, constructing on AM and FM, embrace amplitude shift keying (ASK) and frequency shift keying (FSK).

Inside a system, transmitters and receivers may be packaged collectively as transceivers, which carry out each capabilities. Moreover, system on a chip (SoC) configurations combine microcontrollers with the transceiver to permit protocol administration comparable to knowledge packetization.

figure4_06162025

Determine 4: Illustration of Indicators

Communication protocols are units of guidelines for the change of knowledge between the transmitter and receiver. They guarantee knowledge is transmitted in a constant format, permitting gadgets from completely different producers to speak effectively in the event that they respect the protocol. There are lots of completely different sorts of protocols in use. Essentially the most immediately recognizable communication protocol for a lot of is mobile wi-fi.

Mobile wi-fi is the business driver of the digital wi-fi communication revolution. From its business introduction greater than 30 years in the past for cellular voice communication, digital wi-fi know-how has developed, extending the web to our cellular gadgets. At a look:

The continued evolution of the world-wide mobile knowledge community is pushed by two organizations filling distinct however interconnected roles. The Worldwide Telecommunication Union (ITU), units the general necessities and tips for worldwide cellular telecommunications (IMT) requirements. The third Technology partnership Challenge (3GPP), a worldwide collaboration of economic, requirements, and different organizations, performs research after which develops technical specs for cellular communication applied sciences. The ITU guides, opinions, and approves 3GPP’s specs as worldwide requirements, making certain they meet world necessities.

The 3GPP parallel research and specification course of has maintained a cadence of a specification launch each one to 2 years since 1990. These embrace packet-switched knowledge, which offers “all the time on” connection, eliminating dial up and bettering entry to e-mail and internet providers. LTE Launch 8 carried out an adaptation utilizing QPSK, 16QAM, and 64QAM modulation. Later releases included further modulations. A timeline of commercially recognizable releases is offered within the desk under:

A Timeline of Cell Wi-fi Requirements

12 months

Launch

Title

Options

Modulation / Entry

Downlink Information Fee (bits/sec)

1992

Phase1

2G / GSM

GSM Commercially Provided DCS-1800

GMSK/TDMA

9.6 okay

1997

96

2G / GSM

Circuit Switched Consumer Information

GMSK/TDMA

14.4 okay

1998

97

2.5G / GPRS

Packet Switched Consumer Information

GMSK/TDMA

56-114k

1999

98

2.75G / EDGE

Enhanced GPRS

8PSK/TDMA

384 okay (max)

2000

99

3G / UMTS

W-CDMA  Interface

QPSK/W-CDMA

384 okay

2002

5

3G / UMTS

HSDPA

16QAM/W-CDMA

2-12 M

2008

8

4G / LTE

LTE Launched

OFDMA

5-100M

2018

15

5G / NR

NR Launched

OFDMA

100-1000M

Some further incessantly used wi-fi protocols embrace:

  • Wi-Fi: That is the acquainted wi-fi IEEE 802.11-based protocol that operates within the 2.4 GHz ISM Band with 14 channels spaced 5 MHz aside. In america, channels 1 via 11 are generally used, particularly channels 1, 6 and 11, that are the one non-overlapping channels. Wi-Fi is utilized in properties, metropolis infrastructures, geolocation, industrial environments, and Web of Issues (IoT) purposes.
  • Bluetooth low vitality: That is the acquainted low-power protocol utilized by numerous gadgets for close-proximity communication. It operates within the 2.4 GHz ISM Band. Frequency-hopping unfold spectrum (FHSS) is the modulation method used, and its band is split into 40 2-MHz channels. It’s utilized in sensible residence gadgets, healthcare purposes, location-based providers, and extra.
  • Zigbee: This low-power wi-fi mesh community protocol is below the IEEE 802.15.4 radio specification. It operates on the 868 MHz radio band in Europe, the 915 MHz radio band in North America and Australia, and globally at 2.4 GHz. It will possibly transmit over a distance of as much as 100 meters (line of sight) and might obtain uncooked knowledge throughput charges as much as 500 kbps. Zigbee operates on 16 mounted channels which might be 5 MHz aside within the 2.4 GHz band. It’s primarily utilized in residence automation, sensible vitality, wi-fi sensing and industrial automation.

figure5_06162025

Determine 5: Wi-Fi and Zigbee Channels

How Do Units Talk with One One other?

Units talk by encoding knowledge into modulated alerts on a service wave at a particular frequency. As seen in Determine 5, two Zigbee radios speaking on channel 19 can be speaking on the frequency of 2445 MHz.

Antennas are required in wi-fi communication since they’re chargeable for radiating alerts into the air (i.e., transmitter) and receiving the incoming alerts (i.e., receiver). Antenna designs are decided by the character of the communication utility, the supposed frequencies and modulation methodology, and high quality elements comparable to vary, bandwidth, and working atmosphere.

Multiplexing is a technique that enables a number of transmitted alerts or streams of knowledge to be shared over a single shared communication channel. Frequency division multiplexing permits a number of customers to ship knowledge via a single communication channel by dividing the full channel into a number of sub-channels with non-overlapping service frequencies. These sub-channels are allotted to separate customers or gadgets. For instance, Zigbee, as famous above, operates on 16 channels within the 2.4 GHz vary. Time division multiplexing schemes assist handle entry to a channel by allocating particular person customers or gadgets a particular timeslot for info transfers on the identical shared service frequency to keep away from colliding transmissions. Customers or gadgets transmit in fast succession, every with their very own timeslot. There are additionally extra complicated approaches to multiplexing comparable to code division multiplexing which use superior methods like direct sequence unfold spectrum or frequency-hopping unfold spectrum to permit customers entry to your entire bandwidth for your entire period of transmission by assigning every machine/consumer a novel, orthogonal code.

RF Assaults

RF assaults exploit vulnerabilities to intercept, disrupt, or manipulate programs and related protocols. The results of RF assaults can vary from knowledge breaches and lack of confidentiality to denial of service and disruption of important communications. An instance that illustrates RF safety dangers is railroad and practice jacking, as within the current Poland railway assault stopped 20 trains in 2023. As wi-fi know-how grows, so do the assault discipline and threats.

What Are Widespread Varieties of RF Assaults?

A number of frequent RF assault vectors exploit weaknesses in wi-fi communications. Widespread vectors embrace the next:

  • Eavesdropping includes intercepting and listening to wi-fi communications with out authorization. This will enable a malicious actor to realize entry to delicate info comparable to passwords, authentication processes, private info, or import system processes. Attackers can make the most of software-defined radios (SDRs) to seize and decode transmitted knowledge in a versatile method, enabling attackers to quickly adapt as they study extra about frequencies, modulation methods, and protocols.
  • Replay assaults, that are analogous to man-in-the-middle (MITM) assaults in cybersecurity, happen when an attacker captures legitimate transmissions after which retransmits them to impersonate a respectable machine or consumer. These assaults can bypass authentication or achieve unauthorized entry to programs. For instance, a malicious actor may sniff the transmissions that carry the code from a wise lock to unlock/lock a door or sniff and replay the rolling code from a car’s key fob to acquire entrance to a automotive.
  • Relay assaults improve a sound radio sign and use it to entry a sound goal. In contrast to a replay assault, which captures and resends the sign, a relay assault permits a sign to journey farther and be used at longer distances. Sensible fobs and keys are prone to this kind of assault.
  • Jamming is a denial-of-service assault the place the attacker transmits radio alerts on the identical frequency because the focused communication, successfully disrupting or blocking the respectable alerts. This will forestall gadgets from speaking, which might result in service outages or operational disruptions.

RF Vulnerabilities

On this part, we analyze current examples of notable RF assaults which have been written about within the public press.

Replay Assault

Keyless entry programs have modified how individuals use automotive keys and entry safe areas, changing outdated bodily keys with key fobs. Nonetheless, these programs are weak to RF assaults. Automotive key fobs use RF alerts to ship a code to autos, permitting them to be unlocked and even began. From the late Eighties to early 2000s, keyless entry programs emerged as a premium on a number of vehicles. Like a storage door opener, a button can be pressed on the keyless entry machine, transmitting an RF sign to the automotive, and a code would enable the automotive to be locked or unlocked. With little-to-no safety included of their preliminary design, early keyless entry programs had been weak to cloning and replay assaults. Because the know-how grew to become extra plentiful, safety elevated, including fundamental encryption to keyless entry gadgets and options such because the rolling key methodology. Within the rolling key methodology, a brand new code is generated every time a button is pressed on the important thing fob. With the introduction of rolling keys, fundamental replay assaults not labored as a result of the captured and replayed code didn’t match the newly generated code.

In response to this stronger protection, two new forms of replay assaults emerged, the RollBack assault and the RollJam assault. RollBack captures two alerts: when a key’s pressed, the primary sign is jammed, and the second sign is allowed. The primary sign is then replayed, after which inside 5 seconds, the second sign is replayed to permit entry. Just like the RollBack assault, the RollJam assault captures two alerts. In contrast to RollBack, each alerts one and two are jammed, after which sign one is replayed rapidly, permitting the proprietor entry to the automotive. Then the second sign is replayed later by the attacker.

figure6_06162025

Determine 6: RollJam and RollBack Assaults on Keyless Car Methods

Car theft is a well-liked use of replay assaults. Nonetheless, residence automation programs will also be victims of these kinds of assaults. RF doorbell alerts may be cloned and replayed, as proven on this demonstration.

Relay Assault

Keyless entry programs are actually frequent options on most vehicles, and a brand new premium characteristic has emerged. With keyless automotive fobs, a sign from the important thing fob is all the time transmitting and the proprietor doesn’t must hit a button to unlock the automotive. Just like the replay assault, relay assaults use a tool to seize a radio sign. As an alternative of copying the sign, the machine boosts the sign to a second machine to make it seem to be a key fob is close to the automotive. This assault often requires two individuals. The primary thief stands near the automotive, whereas the second thief is close to the home making an attempt to pay attention for the always-transmitted sign from the important thing fob. As soon as the second thief can get the sign from the important thing fob, they replay that sign to the primary thief. As soon as the primary thief is within the automotive, the second thief will relay one other sign to the primary thief, who’s now capable of begin the automotive.

figure7_06162025

Determine 7: Instruments utilized in replay and relay assaults

Compounding the difficulty, all communication alerts that use radio frequency should register with the Federal Communication Fee (FCC). Key fobs have an FCC ID, which tells the frequency used. There are business instruments out there that enable an attacker to make use of the ID to set the frequency on their machine, simplifying the method since they don’t have to make use of different instruments to scan RF alerts and decide the frequency.

Affiliation Flood Assault

In an affiliation flood assault, an attacker exploits the method by which a brand new Zigbee node joins a community. In a Zigbee community, there’s a coordinator (grasp of the community), a router, and endpoints. The assault begins when a malicious actor replicates the becoming a member of procedures, the place a brand new node sends a beacon request to the coordinator of the community, adopted by an affiliation request. By flooding the coordinator with quite a few pretend requests, the attacker can overwhelm the community. This permits the malicious actor to realize unauthorized entry in a community of residence or workplace gadgets to delicate knowledge, management gadgets, or simply usually trigger disruptions to the Zigbee community.

figure8_06162025

Determine 8: Zigbee Mesh Community Topology

RF Vulnerabilities in Protection Purposes

RF know-how is closely utilized in protection purposes since superior radio know-how is used to hold out operations. Wi-fi communications have performed an integral function in tactical missions and normal warfare and protection operations. Safe alerts are used to guard voice and knowledge communications throughout operations. For instance, Single Channel Floor and Airborne Radio Methods (SINCGARS) are navy programs that present voice and knowledge to command-and-control operations. There are military-specific GPS alerts which might be designed to withstand jamming and assist management the operational atmosphere. Spectrum utilization within the navy area is an important a part of trendy navy operations that assist assist coordination and administration. Whether or not offering voice, knowledge, or cellular ad-hoc networking capabilities to warfighters, RF helps the monitoring of apparatus or autos or coordinating models with plane and drones. It’s a vital device for battle planning.

Spoofing and Jamming in GPS and Radar Methods

GPS alerts, essential for navigation and sustaining dependable positioning knowledge for operations, are an integral part of navy operations. Nonetheless, there was an increase of GPS assaults throughout the previous few years, as these programs may be spoofed or jammed by adversaries. Spoofing includes creating counterfeit alerts that may deceive receivers, comparable to giving an incorrect location. GPS and radar programs are prone to affiliation flood assaults, making your entire community imagine there are extra legitimate nodes then there actually are. The confusion created can be utilized to mislead drones or unmanned aerial autos (UAV) to a improper vacation spot.

GPS spoofing in navy operations is conceptually just like the automotive key fob assault described above. In a GPS spoofing assault, an adversary would possibly use ground-based programs to broadcast false GPS alerts that deceive navy GPS receivers, main them to navigate to incorrect coordinates. Simply as a automotive may be tricked into accepting a replayed key fob sign, navy programs counting on GPS may be misled by a replayed or pretend sign. Equally, an adversary may use an RF jamming machine to intrude with a radar system, stopping it from detecting incoming plane and deceptive radar operators into pondering an incoming plane is coming from a unique location.

In these instances, the vulnerability lies within the transmission of RF alerts with out correct safeguards towards interception, replay, or manipulation. Additional analysis into safeguarding and securing these programs towards dangers with extra anti-jamming methods, superior encryptions, or different pathways will assist guarantee nationwide safety.

Work with the SEI

Understanding RF vulnerabilities and dangers is step one in studying the way to mitigate them. Right here on the SEI, we’re creating instruments and processes to securely harness the facility of RF. For instance, we’re creating machine studying (ML) methods to foretell RF sign power and modulation sorts to assist speed up the aptitude of conventional physics-based modeling and simulation. This elevated velocity can allow purposes at present not possible, comparable to large-scale threat evaluation with uncertainty quantification, design optimization over very massive resolution areas, and extra lifelike real-time war-gaming.

Moreover, the SEI is working to modernize current processes, knowledge, and digital infrastructure by creating software program instruments and knowledge pipelines that assist RF spectrum operations because the disciplines of wi-fi communications and conventional cybersecurity operations proceed to maneuver in direction of convergence. In case you are keen on studying extra about this work or collaborating with the SEI, please contact us.

Will AI Exchange Software program Engineers? Detailed Overview


How typically have you ever caught your self pondering, “Wouldn’t it’s simpler at hand the mission over to AI as an alternative of paying a staff of builders?” It’s a tempting thought, particularly within the age of AI — however the actuality is much extra advanced.

On this article, we’ll discover what AI can really do in software program improvement, the place it nonetheless falls brief in comparison with people, and what conclusions firms ought to draw earlier than entrusting a mission to synthetic intelligence.

When AI Tried to Play Software program Engineer

Not too long ago, a shopper approached SCAND with a novel experiment in thoughts. They needed to check whether or not synthetic intelligence may independently develop a small internet utility and determined to make use of Cursor for the duty. The applying’s function was easy — fetch statistics from an exterior API and show them in a desk.

The preliminary end result appeared promising: AI created a functioning mission that included each client- and server-side elements, applied the fundamental logic for retrieving information, and even designed the interface. The desk appropriately displayed the statistics, and the general code construction appeared respectable at first look.

Nonetheless, upon nearer inspection, it turned clear that the answer was overengineered. As an alternative of instantly connecting to the API and displaying the information within the browser, AI constructed a full backend server that proxied requests, saved intermediate information, and required separate deployment.

For such a easy job, this was pointless — it difficult the infrastructure, added additional setup steps, and lengthened the combination course of.

Furthermore, AI didn’t account for error dealing with, request optimization, or integration with the shopper’s current programs. This meant builders needed to step in and redo components of the answer.

The Limits of Generative AI in Coding and Software program Improvement

Generative AI has already confirmed that it could possibly rapidly produce working code, however in apply, its capabilities in real-world software program improvement typically change into restricted. Listed below are the important thing points we recurrently encounter when reviewing AI‑generated initiatives:

AI-generated code

  • Lack of awareness of enterprise logic and structure. AI can’t see the complete image of a mission, its objectives, and its constraints. Consequently, the options it produces could also be technically appropriate however fully misaligned with the precise enterprise wants.
  • Incapacity to make architectural commerce‑offs. An skilled software program engineer evaluates the steadiness between improvement velocity, implementation value, and ease of upkeep. AI, however, can’t weigh these elements and tends to decide on a normal and even unnecessarily advanced strategy.
  • Overengineering. Producing pointless layers, modules, and providers is a typical mistake. For instance, a easy utility could find yourself with an additional backend that requires separate deployment and upkeep.
  • Ignoring the context of current programs. AI doesn’t take into consideration how new code will combine with the present infrastructure, which may result in incompatibilities or further prices for rework.
  • Code ≠ product. Synthetic intelligence can write fragments of code, however it doesn’t ship full options that take into consideration UX, safety, scalability, and long-term assist.
  • Doesn’t at all times absolutely perceive the duty. To get the specified end result, prompts typically should be clarified or rewritten in additional element — generally stretching to a full web page. This slows down the method and forces the developer to spend time refining the request as an alternative of transferring on to efficient implementation.

In the end, regardless of the rising position of AI in software program improvement, with out the involvement of skilled builders, such initiatives danger changing into a supply of technical debt and pointless prices.

Why Human Software program Builders Nonetheless Beat AI Brokers

Sure, generative AI and agentic AI can write code as we speak — generally even pretty good code. However there are nonetheless some issues that synthetic intelligence can’t exchange in knowledgeable software program developer’s workflow..

First, it’s understanding the enterprise context. A human doesn’t simply write a program — they know why and for whom it’s being created. AI sees a set of directions; a developer sees the actual job and understands the way it suits into the corporate’s objectives.

Second comes the power to make knowledgeable choices — whether or not to reuse current code or construct one thing from scratch. A human weighs deadlines, prices, and dangers. AI, in flip, typically follows a template with out taking hidden prices into consideration.

Third, it’s architectural flexibility. An skilled programmer can really feel when a mission is beginning to “develop” pointless layers and is aware of when it’s the suitable time to cease. AI, however, typically creates extreme buildings just because that’s what it has seen in its coaching examples.

Fourth comes desirous about the product’s future. Scalability, maintainability, and dealing with edge circumstances are constructed right into a developer’s mindset. AI will not be but able to anticipating such nuances.

And eventually, communication. A real software program engineer works with the shopper, clarifies necessities, and adjusts the strategy because the mission evolves. AI will not be able to actual dialogue or a delicate understanding of human priorities.

Due to this fact, in as we speak’s software program improvement panorama, synthetic intelligence continues to be a software — not a strategist. And within the foreseeable future, the human position in creating excessive‑high quality software program will stay important.

The desk under compares how people and AI deal with key points of improvement, and why the human position within the course of continues to be necessary.

Criterion Software program Developer Generative AI
Understanding enterprise context Analyzes mission objectives, target market, and long-term targets Sees solely the given immediate, with out understanding the larger image
Making architectural choices Balances velocity, value, simplicity, and maintainability Follows a template with out contemplating hidden prices
Structure optimization Avoids pointless modules and simplifies when doable Liable to overengineering, creating additional layers
Working with current programs Considers integration with present infrastructure Might generate incompatible options
Foresight Plans for scalability, error dealing with, and edge circumstances Typically ignores non‑normal eventualities
Collaboration Engages with the shopper, clarifies necessities, affords alternate options Understands the request in a restricted method, requires exact and detailed prompts
Flexibility in course of Adapts to altering necessities on the fly Requires code regeneration or a brand new immediate
Velocity of code technology Focuses on correctness and stability over uncooked velocity Generates code immediately, however it’s not at all times helpful or appropriate
Last deliverable Prepared‑to‑use product A set of code requiring evaluate and refinement

 Human Builders vs AI in Software program Improvement

The place AI Coding Instruments and Agentic AI Can Assist Software program Engineers

Regardless of its limitations, AI instruments have some strengths that make them precious assistants for software program engineers. In keeping with Statista (2024), 81% of builders worldwide reported elevated productiveness when utilizing AI, and greater than half famous improved work effectivity.

ai

Advantages of utilizing AI within the improvement workflow, Statista

In day‑to‑day improvement, AI can considerably velocity up routine duties and simplify supporting processes, akin to:

  • Producing boilerplate code. Generative AI can produce repetitive code buildings in seconds, saving time and permitting builders to give attention to enterprise logic.
  • Creating easy elements. AI can rapidly construct buttons, types, tables, and different UI components that may later be tailored to the mission’s wants.
  • Changing codecs. Synthetic intelligence can simply remodel information and code — from JSON to YAML or from TypeScript to JavaScript, and again.
  • Refactoring. AI can counsel code enhancements, simplify buildings, and take away duplicates.
  • Speedy prototyping. AI can construct a primary model of performance to check concepts or exhibit ideas to a shopper.

Nonetheless, even in these use circumstances, AI stays only a software. The ultimate model of the code ought to at all times undergo human evaluate and integration to make sure it meets architectural necessities, high quality requirements, and the mission’s enterprise context.

Ai

SCAND’s Method — AI + Human Experience within the Age of AI

At SCAND, we see synthetic intelligence not as a competitor to builders, however as a software that strengthens the staff. Our initiatives are constructed on a easy precept: AI accelerates — people information.

We use Copilot, ChatGPT, Cursor, and different AI instruments the place they really add worth — for rapidly creating templates, producing easy elements, and testing concepts. This enables us to save hours and days on routine duties.

However code technology is barely the start. Each AI‑produced answer goes by means of the arms of our skilled builders who:

  • Verify the correctness and safety of the code, together with potential license and copyright violations, since some items of the urged code could replicate fragments from open repositories.
  • Optimize the structure for the duty and mission specifics.
  • Adapt technical options to the enterprise logic and mission necessities.

We additionally pay particular consideration to information safety and confidentiality:

  • We don’t switch confidential information to public cloud-based AI with out safety, until the shopper particularly requests in any other case. In initiatives involving delicate or regulated data (for instance, medical or monetary information), we use native AI assistants — Ollama, LM Studio, llama.cpp, and others — deployed on the shopper’s safe servers.
  • We signal clear contracts that specify: who owns the ultimate code, whether or not AI instruments are allowed, and who’s chargeable for reviewing and fixing the code if it violates licenses or incorporates errors.
  • We embody obligations for documentation (AI utilization logs indicating when precisely and which instruments have been used) to trace the supply of potential points and guarantee transparency for audits.
  • We offer staff coaching on AI greatest practices, together with understanding the constraints of AI-generated content material, licensing dangers, and the significance of handbook validation.

Will AI Exchange Software program Engineers? The Sensible Actuality Verify

In the present day, synthetic intelligence in software program improvement is on the identical degree that calculators have been in accounting a number of many years in the past: a software that hurries up calculations, however doesn’t perceive why and what numbers should be calculated.

Generative AI can already do rather a lot — from producing elements to performing computerized refactoring. However constructing a software program product isn’t just about writing code. It’s about understanding the viewers, designing structure, assessing dangers, integrating with current programs, and planning lengthy‑time period assist for years forward. And that is the place the human issue stays irreplaceable.

As an alternative of the “AI replaces builders” situation, we’re transferring towards a blended‑staff mannequin, the place AI brokers turn into a part of the workflow and builders use them as accelerators and assistants. This synergy is already reshaping the software program improvement panorama and can proceed to outline it within the coming years.

The primary takeaway: the age of AI doesn’t eradicate the occupation of software program engineer — it transforms it, including new instruments and shifting priorities from routine coding towards structure, integration, and strategic design.

Regularly Requested Questions (FAQs)

Can AI write a whole app?

Sure, however typically with out optimization, with over‑engineered structure, and with out contemplating lengthy‑time period maintainability.

Will AI exchange frontend/backend builders?

Not but, since most improvement choices require enterprise context, commerce‑offs, and expertise that AI doesn’t possess.

What’s the largest influence of AI-generated code?

An elevated danger of technical debt, maintainability points, and architectural misalignment — all of which may finally drive up the price of rework.

Android Builders Weblog: What’s HDR?



Android Builders Weblog: What’s HDR?

Posted by John Reck – Software program Engineer

For Android builders, delivering distinctive visible experiences is a steady aim. Excessive Dynamic Vary (HDR) unlocks new prospects, providing the potential for extra vibrant and immersive content material. Applied sciences like UltraHDR on Android are significantly compelling, offering the advantages of HDR shows whereas sustaining essential backwards compatibility with SDR shows. On Android you should utilize HDR for each video and pictures.

Through the years, the time period HDR has been used to indicate quite a lot of associated, however finally distinct visible constancy options. Customers encounter it within the context of digital camera options (publicity fusion), or as a advertising and marketing time period in TV or monitor (“HDR succesful”). This conflates distinct options like wider colour gamuts, elevated bit depth or enhanced distinction with HDR itself.

From an Android Graphics perspective, HDR primarily signifies larger peak brightness functionality that extends past the traditional Commonplace Dynamic Vary. Different perceived advantages usually derive from requirements comparable to HDR10 or Dolby Imaginative and prescient which additionally embrace the utilization of wider colour areas, larger bit depths, and particular switch features.

On this article, we’ll set up the foundational colour rules, then deal with frequent myths, make clear HDR’s position within the rendering pipeline, and study how Android’s show applied sciences and APIs allow HDR expertise.

The elements of colour

Understanding HDR begins with defining the three major elements that type the displayed quantity of colour: bit depth, switch perform, and colour gamut. These describe the precision, scaling, and vary of the colour quantity, respectively.

Whereas a colour mannequin defines the format for encoding pixel values (e.g., RGB, YUV, HSL, CMYK, XYZ), RGB is usually assumed in a graphics context. The mix of a colour mannequin, a colour gamut, and a switch perform constitutes colour area. Examples embrace sRGB, Show P3, Adobe RGB, BT.2020, or BT.2020 HLG. Quite a few combos of colour gamut and switch perform are attainable, resulting in quite a lot of colour areas.

components of color include bit depth + transfer fn + color gamut + color model with the last three being within the color space

Elements of colour

Bit Depth

Bit depth defines the precision of colour illustration. A better bit depth permits for finer gradation between colour values. In trendy graphics, bit depth sometimes refers to bits per channel (e.g., an 8-bit picture makes use of 8 bits for every crimson, inexperienced, blue, and optionally alpha channel).

Crucially, bit depth doesn’t decide the general vary of colours (minimal and most values) a picture can characterize; that is set by the colour gamut and, in HDR, the switch perform. As a substitute, rising bit depth gives extra discrete steps inside that outlined vary, leading to smoother transitions and lowered visible artifacts comparable to banding in gradients.

5-bit

5-bit color gradient showing distinct transition between color values

8-bit

8-bit color gradient showing smoother transition between color values

Though 8-bit is among the most typical codecs in widespread utilization, it’s not the one choice. RAW photographs may be captured at 10, 12, 14, or 16 bits. PNG helps 16 bits. Video games regularly use 16-bit floating level (FP16) as a substitute of integer area for intermediate render buffers. Trendy GPU APIs like Vulkan even assist 64-bit RGBA codecs in each integer and floating level varieties, offering as much as 256-bits per pixel.

Switch Operate

A switch perform defines the mathematical relationship between a pixel’s saved numerical worth and its closing displayed luminance or colour. In different phrases, the switch perform describes find out how to interpret the increments in values between the minimal and most. This perform is important as a result of the human visible system’s response to gentle depth is non-linear. We’re extra delicate to adjustments in luminance at low gentle ranges than at excessive gentle ranges. Due to this fact, a linear mapping from saved values to show luminance wouldn’t lead to an environment friendly utilization of the obtainable bits. There could be greater than vital precision within the brighter area and too little within the darker area with respect to what’s perceptual. The switch perform compensates for this non-linearity by adjusting the luminance values to match the human visible response.

Whereas some switch features are linear, most make use of advanced curves or piecewise features to optimize picture high quality for particular shows or viewing circumstances. sRGB, Gamma 2.2, HLG, and PQ are frequent examples, every prioritizing bit allocation in a different way throughout the luminance vary.

Shade Gamut

Shade gamut refers back to the whole vary of colours {that a} explicit colour area or gadget can precisely reproduce. It’s sometimes a subset of the seen colour spectrum, which encompasses all the colours that the human eye can understand. Every colour area (e.g., sRGB, Show P3, BT2020) defines its personal distinctive gamut, establishing the boundaries for colour illustration.

A wider gamut signifies that the colour area can show a better number of colours, resulting in richer and extra vibrant photographs. Nevertheless, merely having a bigger gamut would not at all times assure higher colour accuracy or a extra vibrant outcome. The gadget or medium used to show the colours should even be able to reproducing the total vary of the gamut. When a show encounters colours exterior its reproducible gamut, the standard dealing with technique is clipping. That is to make sure that in-gamut colours are correctly preserved for accuracy, as in any other case makes an attempt to scale the colour gamut might produce disagreeable outcomes, significantly in areas through which human imaginative and prescient is especially delicate like pores and skin tones.

HDR myths and realities

With an understanding of what kinds the fundamental working colour rules, it’s now time to guage a few of the frequent claims of HDR and the way they apply in a normal graphics context.

Declare: HDR presents extra vibrant colours

This declare comes from HDR video sometimes utilizing the BT2020 colour area, which is certainly a large colour quantity. Nevertheless, there are a number of issues with this declare as a blanket assertion.

The primary is that photographs and graphics have been ready to make use of wider colour gamuts, comparable to Show P3 or Adobe RGB, for fairly a very long time now. This isn’t a singular development that was coupled to HDR. In JPEGs for instance that is outlined by the ICC profile, which dates again to the early Nineteen Nineties, though wide-spread adoption of ICC profile dealing with is considerably more moderen. Equally on the graphics rendering facet the utilization of wider colour areas is absolutely decoupled from whether or not or not HDR is getting used.

The second is that not all HDR movies even use such a wider gamut in any respect. Though HDR10 specifies the utilization of BT2020, different HDR codecs have since been created that don’t use such a large gamut.

The most important situation, although, is considered one of capturing and displaying. Simply because the format permits for the colour gamut of BT2020 doesn’t imply that your complete gamut is definitely usable in follow. For instance present Dolby Imaginative and prescient mastering pointers solely require a 99% protection of the P3 gamut. Which means that even for high-end skilled content material, it’s not anticipated that the authoring of content material past that of Show P3 is feasible. Equally, the overwhelming majority of shopper shows immediately are solely able to displaying both sRGB or Show P3 colour gamuts. On condition that the standard advice of out-of-gamut colours is to clip them, which means that regardless that HDR10 permits for as much as BT2020 gamut, the widest gamut in follow continues to be going to be P3.

Thus this declare ought to actually be thought of one thing supplied by HDR video profiles when in comparison with SDR video profiles particularly, though SDR movies may use wider gamuts if desired with out utilizing an HDR profile.

Declare: HDR presents extra distinction / higher black element

One of many advantages of HDR typically claimed is darkish blacks (e.g. Dolby Imaginative and prescient Demo #3 – Core Universe – 4K HDR or “Darkish scenes come alive with darker darks” ) or extra element at nighttime areas. That is even mirrored in BT.2390: “HDR additionally permits for decrease black ranges than conventional SDR, which was sometimes within the vary between 0.1 and 1.0 cd/m2 for cathode ray tubes (CRTs) and is now within the vary of 0.1 cd/m2 for most traditional SDR liquid crystal shows (LCDs).” Nevertheless, in actuality no show makes an attempt to indicate something however SDR black because the blackest black the show is bodily able to. Thus there is no such thing as a distinction between HDR or SDR when it comes to how darkish it could possibly attain – each backside out on the similar darkish stage on the identical show.

As for distinction ratio, as that’s the ratio between the brightest white and the darkest black, it’s overwhelmingly influenced by how darkish a show can get. With the prevalence of OLED shows, significantly within the cell area, each SDR and HDR have the identical distinction ratio consequently, as they each have basically excellent black ranges giving them infinite distinction ratios.

The PQ switch perform does allocate extra bits to the darkish area, so in idea it could possibly convey higher black element. Nevertheless, it is a distinctive side of PQ moderately than a characteristic of HDR. HLG is more and more the extra frequent HDR format as it’s most well-liked by cell cameras in addition to a number of excessive finish cameras. And whereas PQ might include this element, that doesn’t imply the HDR show can essentially show it anyway, as mentioned in Show Realities.

Declare: HDR presents larger bit depth

This declare comes from HDR10 and a few, however not all, Dolby Imaginative and prescient profiles utilizing 10 or 12-bits for the video stream. Just like extra vibrant colours, that is actually simply a facet of explicit video profiles moderately than one thing HDR itself inherently gives or is coupled to HDR. The utilization of 10-bits or extra is in any other case not unusual in imaging, significantly within the larger finish images world, with RAW and TIFF picture codecs able to having 10, 12, 14, or 16-bits. Equally, PNG helps 16-bits, though that’s hardly ever used.

Declare: HDR presents larger peak brightness

This then, is all that HDR actually is. However what does “larger peak brightness” actually imply? In any case, SDR shows have been pushing ever rising brightness ranges earlier than HDR was important, significantly for daylight viewing. And even with out that, what’s the distinction between “HDR” and simply “SDR with the brightness slider cranked up”? The reply is that we outline “HDR” as having a brightness vary greater than SDR, and we consider SDR as being the vary pushed by autobrightness to be comfortably readable within the present ambient circumstances. Thus we outline HDR when it comes to issues like “HDR headroom” or “HDR/SDR ratio” to point it’s a floating area relative to SDR. This makes brightness insurance policies simpler to motive about. Nevertheless, it does complicate the interplay with conventional HDR comparable to that utilized in video, particularly HLG and PQ content material.

PQ/HLG switch features

PQ and HLG characterize the 2 most typical approaches to HDR when it comes to video content material. They characterize two switch features that characterize totally different ideas of what’s “HDR.” PQ, revealed as SMPTE ST 2084:2014, is outlined when it comes to absolute nits within the show. The expectation is that it encodes from 0 to 10,000 nits, and expects to be mastered for a selected reference viewing atmosphere. HLG takes a special method, as a substitute opting to take a typical gamma curve for a part of the vary earlier than switching to logarithmic for the brighter portion. This has a claimed nominal peak brightness of 1000 nits within the reference atmosphere, though it’s not outlined in absolute luminance phrases like PQ is.

Trade-wide specs have not too long ago formalized the brightness vary of each PQ- and HLG-encoded content material in relation to SDR. ITU-R BT. 2408-8 defines the reference white stage for graphics to be 203 nits. ISO/TS 22028-5 and ISO/PRF 21496-1 have adopted go well with; 21496-1 particularly defines HDR headroom when it comes to nominal peak luminance, relative to a diffuse white luminance at 203 nits.

The realities of contemporary shows, mentioned under, in addition to typical viewing environments imply that conventional HDR video are almost by no means displayed as supposed. A show’s HDR headroom might evaporate underneath brilliant viewing circumstances, demanding an on-demand tonemapping into SDR. Conventional HDR video encodes a set headroom, whereas trendy shows make use of a dynamic headroom, leading to huge variations in video high quality even on the identical show.

Show Realities

To this point many of the dialogue round HDR has been from the angle of the content material. Nevertheless, customers eat content material on a show, which has its personal capabilities and extra importantly limits. A high-end cell show is prone to have traits comparable to gamma 2.2, P3 gamut, and a peak brightness of round 2000 nits. If we then think about one thing like HDR10 there are mismatches in bit utilization prioritization:

    • PQ’s elevated bit allocation on the decrease ranges finally ends up being wasted
    • The utilization of BT2020 finally ends up spending bits on components of a gamut that may by no means be displayed
    • Encoding as much as 10,000 nits of brightness is equally headroom that’s not utilized

These mismatches will not be inherently an issue, nevertheless, but it surely implies that as 10-bit shows grow to be extra frequent the prevailing 10-bit HDR video profiles are unable to truly benefit from the total show’s capabilities. Thus HDR video profiles are ready of concurrently being ahead wanting whereas additionally already being unable to maximise a present 10-bit show’s capabilities. That is the place know-how comparable to Extremely HDR or gainmaps typically present a compelling different. Regardless of typically utilizing an 8-bit base picture, as a result of the achieve layer that transforms it to HDR is specialised to the content material and its explicit vary wants it’s extra environment friendly with its bit utilization, resulting in outcomes that also look gorgeous. And as that base picture is upgraded to 10-bit with newer picture codecs comparable to AVIF, the efficient bit utilization is even higher than these of typical HDR video codecs. Thus these approaches don’t characterize evolutionary or stepping stones to “true HDR”, however moderately are additionally an enchancment on HDR along with having higher backwards compatibility. Equally Android’s UI toolkit’s utilization of the extendedRangeBrightness API truly nonetheless primarily occurs in 8-bit area. As a result of the rendering is tailor-made to the particular show and present circumstances it’s nonetheless attainable to have an excellent HDR expertise regardless of the utilization of RGBA_8888.

Unlocking HDR on Android: Subsequent steps

Excessive Dynamic Vary (HDR) presents development in visible constancy for Android builders, transferring past the normal constraints of Commonplace Dynamic Vary (SDR) by enabling larger peak brightness.

By understanding the core elements of colour – bit depth, switch perform, and colour gamut – and debunking frequent myths, builders can leverage applied sciences like Extremely HDR to ship actually immersive experiences which are each visually gorgeous and backward suitable.

In our subsequent article, we’ll delve into the nuances of HDR and consumer intent, exploring find out how to optimize your content material for various show capabilities and viewing environments.

OpenAI releases two open weight reasoning fashions


OpenAI is becoming a member of the open weight mannequin recreation with the launch of gpt-oss-120b and gpt-oss-20b. 

Gpt-oss-120b is optimized for manufacturing, excessive reasoning use circumstances, and gpt-oss-20b is designed for decrease latency or native use circumstances. 

In line with the corporate, these open fashions are similar to its closed fashions by way of efficiency and functionality, however at a a lot decrease value. For instance, gpt-oss-120b working on an 80 GB GPU achieved related efficiency to o4-mini on core reasoning benchmarks, whereas gpt-oss-20b working on an edge machine with 16 GB of reminiscence was similar to o3-mini on a number of frequent benchmarks. 

“Releasing gpt-oss-120b and gpt-oss-20b marks a major step ahead for open-weight fashions,” OpenAI wrote in a put up. “At their measurement, these fashions ship significant developments in each reasoning capabilities and security. Open fashions complement our hosted fashions, giving builders a wider vary of instruments to speed up vanguard analysis, foster innovation and allow safer, extra clear AI growth throughout a variety of use circumstances.”

The brand new open fashions are perfect for builders who need to have the ability to customise and deploy fashions in their very own surroundings, whereas builders searching for multimodal assist, built-in instruments, and integration with OpenAI’s platform could be higher suited with the corporate’s closed fashions. 

Each new fashions can be found below the Apache 2.0 license, and are suitable with OpenAI’s Responses API, can be utilized inside agentic workflows, and supply full chain-of-thought.

In line with OpenAI, these fashions have been educated utilizing its superior pre- and post-training methods, with a concentrate on reasoning, effectivity, and real-world usability in numerous kinds of deployment environments. 

Each fashions can be found for obtain on Hugging Face and are quantized in MXFP4 to allow gpt-oss-120B to run with 80 GB of reminiscence and gpt-oss-2bb to run with 16 GB. OpenAI additionally created a playground for builders to experiment with the fashions on-line. 

The corporate partnered with a number of deployment suppliers for these fashions, together with Azure, vLLM, Ollama, llama.cpp, LM Studio, AWS, Fireworks, Collectively AI, Baseten, Databricks, Vercel, Cloudflare, and OpenRouter. It additionally labored with NVIDIA, AMD, Cerebras, and Groq to assist guarantee constant efficiency throughout completely different programs. 

As a part of the preliminary launch, Microsoft will probably be offering GPU-optimized variations of the smaller mannequin to Home windows units. 

“A wholesome open mannequin ecosystem is one dimension to serving to make AI extensively accessible and useful for everybody. We invite builders and researchers to make use of these fashions to experiment, collaborate and push the boundaries of what’s potential. We look ahead to seeing what you construct,” the corporate wrote.

ios – How am i able to implement undoManager and make undo(), redo() capabilities?


I have to create undo and redo performance utilizing swift UndoManager to my Paint app. I did it undo with eradicating final oject from array. However i need to use UndoManager. And if there’s some advices, possibly i’m doing one thing improper. If somebody may also help me, pls.

remaining class WACanvas: UIView {

    non-public var strains = [WALine]()
    non-public var strokeColor = UIColor.black
    non-public var strokeWidth: Float = 1
    
    override func draw(_ rect: CGRect) {
        tremendous.draw(rect)
        
        guard let context = UIGraphicsGetCurrentContext() else { return }
        
        strains.forEach { line in
            guard line.factors.rely > 1 else { return }
            print(line.factors)
            context.setStrokeColor(line.coloration.cgColor)
            context.setLineWidth(CGFloat(line.width))
            context.setLineCap(.spherical)
            
            context.transfer(to: line.factors.first!)
            context.addLines(between: line.factors)
            context.strokePath()
        }
    }
    
    override func touchesBegan(_ touches: Set, with occasion: UIEvent?) {
        strains.append(WALine(coloration: strokeColor, width: strokeWidth, factors: []))
    }

    override func touchesMoved(_ touches: Set, with occasion: UIEvent?) {
        guard let level = touches.first?.location(in: self) else { return }
        
        guard var lastLine = strains.popLast() else { return }
        lastLine.factors.append(level)
        
        strains.append(lastLine)
        
        setNeedsDisplay()
    }
    
    // MARK: - Public strategies
    public func undo() {
        _ = strains.popLast()
        setNeedsDisplay()
    }
    
    public func clear() {
        strains.removeAll()
        setNeedsDisplay()
    }
    
    public func setSTrokeColor(coloration: UIColor) {
        self.strokeColor = coloration
    }
    
    public func setSTroke(width: Float) {
        self.strokeWidth = width
    }
}