₦airaland Forum

airsaylongcome:
So Linux basically. Yeah true.

Not easy to learn robotics in Naija sha. Hardware costs dey put people off

Edit: While Pis are the behomoth in that space, there are loads of other Single Board computers (Banana Pi, Odroid etc) that can also play the role.

Arduino Ventuno Q a platform for systems that interact with the physical environment: robots, autonomous devices, and sensor complexes the capacity is 40 TOPS.

Alphabyte3:
Self-hosting a Linux server

choose a distro, set up hardware/VM, secure it, configure storage (RAID, LVM, ZFS, NAS), pick apps (Syncthing, Immich, Plex, Tailscale), use Docker/Docker Compose, Proxmox/ESXi/XCP-ng/hyperV for virtualization. Configure networking (Mikrotik/Unifi), regularly update, monitor logs, troubleshoot. Popular options: Docker, Portainer, Syncthing, Immich, Plex. Affordable networking: Mikrotik, Unifi

The ultimate datacenter management solution for Proxmox VE and XCP-NG. Unified multi-cluster control, intelligent load balancing, and seamless cross-cluster VM migrations — all in one beautiful interface.


https://github.com/PegaProx/project-pegaprox/releases/tag/v0.9.1

Blender is a free, open-source 3D computer graphics software suite used for modeling, animation, rendering, VFX, and video editing, popular among professionals and hobbyists alike. It supports the entire 3D pipeline and runs on Windows, macOS, and Linux. 


Blender shortcuts or hotkeys


- G: Move
- R: Rotate
- S: Scale
- Tab: Toggle Edit/Object Mode
- Shift+A: Add Object
- E: Extrude
- Ctrl+R: Loop Cut
- I: Inset
- X: Delete
- Numpad 1/3/7: Views
- Z: Shading




https://www.youtube.com/watch?v=4haAdmHqGOw?si=jOu_eqcf9_-Mw3lV

Creating virtual LLM anatomy in 3d mapping the whole body.

Building a quantum simulation os(operating system)for chemicals , drugs and materials discoveries. It could also have a advanced pattern recognition AI to solve quantum problems using quantum datasets and behaviors . The computer the computer would be hybrid quantum and super following HPC requirements.

Laser Internet uses light (lasers) to transmit data wirelessly . Like fibre optics but through air/space, not cables . Faster & more secure than traditional wireless . Used in space comms (satellites) .

The limitations are it requires direct line of sight and can be affected by weather conditions such as fog, rain, or snow. This kind of tech is from direct energy from Laser connected to cover some area but the range are smaller than others but it is promising.
Lasers transmitter might be made cheaper if China and the US perfect it

CCNA and CompTIA are essential if you want to go far in networking. But not it is different from computing because networking is just small fraction of computing you can work in the big industries like Nvidia, AMD , Micron, Google,Intel, TSMC ,Broadcom ,Samsung ,SK Hynix ,ARM ,ASML and Qualcomm.

It depends on your abilities to learn, innovate and create in the process you earn the industry is valuable overseas .

Internet: global network connecting billions of devices (phones, computers, IoT, servers) via wired/wireless tech. Combines space satellites, ground stations, transmitters/towers, OpenRAN, datacenter servers, and end-user devices for seamless connectivity .



This is an open-source 5G RAN solution ! Developed by SRS, it's ORAN-native CU/DU with L1/2/3 implementation and minimal dependencies 📡. Provides complete 5G RAN, portable across architectures (x86, ARM), flexible deployment (monolithic or split CU/DU). As of Dec 2025, it's archived and transitioned to OCUDU repo . For researchers, devs, and operators to experiment/deploy 5G RAN . Includes build guides, deployment on Linux.


The connection is from ISP,router than devices as given as the basis knowledge of networking . To connect devices on different network you can use Cisco packet tracer , cables,Nvidia Nvlink or optical fiber . Africa don't have fab for it but will can buy the things from China or Europe (Siemens or ASML)


https://github.com/srsran/srsRAN_Project

Ide

CLion and VsCode
And C++ complier suitable

I am creating my own in Claude code and other AI and it is great. Still working on it is has inbuilt sentinel detection of threat and disasters.

A complete features to integrate to become more sustainable and usable.

Google 3D Tiles + CesiumJS + OpenSky Network + ADS-B Exchange = ultimate tracking power . We're talking:
- Real-time flight data (6,700+ planes)
- Military flight tracking
- Live satellite tracking (every satellite!)
- Street traffic simulation
- Real-time CCTV camera feeds with IP camera feeds protocol
- Earthquake & seismic data
- Plus CRT, Night Vision & FLIR modes
- AI reporting system

Stephen0mozzy:
Madt project mehn!!! I'm imagining the amount of integration that went into it 😅.

But the live project dey suck data o. All the videos streaming concurrently, multiple api calls for real-time data etc

If the project becomes more usable it need something like ip camera feeds map protocol not embedded YouTube public feeds . I am just observing the code .

Stephen0mozzy:
Madt project mehn!!! I'm imagining the amount of integration that went into it 😅.

But the live project dey suck data o. All the videos streaming concurrently, multiple api calls for real-time data etc

I saw the project last year but the developer used AI and added something to it I can't remember our discussion. He used Claude code or Codex to design something.


He told me that they already have it in their country.

Stephen0mozzy:
Madt project mehn!!! I'm imagining the amount of integration that went into it 😅.

But the live project dey suck data o. All the videos streaming concurrently, multiple api calls for real-time data etc

I saw the project last year but the developer used AI and added something to it I can't remember our discussion. He used Claude code or Codex to design somethings.


He told me that they already have it in their country.

Rust was use tauri is for desktop (windows , Mac and Linux) they used it because it is light weight just like webview. With the Web components it is easier for mobile development and additional features.

budaatum:
Open source too, so available for tweaking.

https://github.com/koala73/worldmonitor?tab=readme-ov-file

Yes you can add Google mapping interface for traffic jam detection and Mobile app for it using anything else you like AI reporting features. This is great this is the type of project palantir are building.

Imagine fine-tune or train it with Nigerian news feeds and camera feeds. Making digital intelligence gathering more compact.

A developer just open-sourced a AI powered real-time global intelligence dashboard , news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface.

It's MIT licensed. 🔓

GTCA encoding and decoding is a method of converting digital data (binary 0s and 1s) into synthetic DNA sequences (Adenine, Cytosine, Guanine, Thymine) for long-term storage, and vice versa.



Binary Conversion files (text, images, etc.) are first converted to binary code. Mapping Rule are digital bits are mapped to DNA bases. A common mapping is 2 bits per base, such as:
00 =C (Cytosine)
01 =T (Thymine)
10= A(Adenine)
11= G (Guanine)


Example: Binary "10001101" becomes "ACGT".


Creating an LLM of different sequence Maker for analysis.

Alphabyte3:
Quantum computing has numerous applications beyond simulation, transforming industries and reshaping the future. Here are some key areas where quantum computing is making an impact.
-Cryptography and Security
- Optimization Problems
- Machine Learning and AI
- Drug Discovery and Healthcare
- Financial Modeling and Risk Analysis.
- Materials Science


- Weather Forecasting
- Blockchain technologies
- Quantum benchmarking system scaling
- space exploration
- autonomous intelligent devices
- Traffic Optimization: Quantum algorithms optimize traffic flow, reducing congestion and emissions.

Stop building prototypes but build multipurpose quantum computers using the HPC requirements enhancing efficiency .

Google DeepMind's unifying model for deciphering the regulatory code within DNA sequences. AlphaGenome offers multimodal predictions, encompassing diverse functional outputs including gene expression, splicing patterns, chromatin features, and contact maps .

The model analyzes up to 1 million base pairs of DNA sequence and can deliver predictions at single base-pair resolution for most modalities. AlphaGenome achieves state-of-the-art performance across a range of genomic prediction benchmarks, including diverse variant effect prediction tasks.



The encoding is in GCTA (Genome-wide Complex Trait Analysis). AlphaGenome adds to the collection of other AI tools developed by Google DeepMind, which includes the 2024 Nobel prize winning AlphaFold that predicts the 3D shape of proteins. Pushmeet Kohli, who led the work, explains that ‘the genome is the recipe and understanding the effect of changing any part of the recipe is what AlphaGenome looks at’.

AlphaGenome turns genetic code into decipherable language of discovery Using a GTCA encoding and decoding of DNA strands.

Samsung's HBM4 is making waves in the AI scene! It's all about boosting memory bandwidth to keep up with AI's growing compute needs. Here's the details:

- HBM4 promises up to 11.7 Gbps data transfer speeds (peaking at 13 Gbps), a 22% jump from HBM3E.
- Built on 4nm logic, it's designed to feed AI GPUs faster and more efficiently.
- Competitors like SK Hynix and Micron are hot on Samsung's heels, with Micron targeting 2.0 TB/s bandwidth per stack.
- The real challenge? Scaling HBM4 production while managing thermal and packaging complexities. This is just vertical and horizontal stacking of 3d chips.
- Whoever masters high-bandwidth memory could dominate the AI boom! What's your take on HBM4's impact on AI development?

Alphabyte3:
There are 4 types of coin according to growth

1. Geometric progression coin gp coin (very fast)

2. Arithmetics progression coin Ap coin (fast)

3. Micro coin (slow)

4. Retrogressive coin (stable or stagnant coin)

Examples

GP coin (BTC ,BNB,ICP BCH,ETH,SOL,TRB,YFI,LTC,Avax,Avve )

AP coin (XRP ,TRX,ADA ,NKN)

Micrcoin (hot ,dent ,win)

Retrogressive coin (USDT ,BUSD)



Here are four crypto coin categories according to growth

1. GP Coin: High-value coins with prices ranging from $10 to $1,000.


2. AP Coin: Mid-value coins with prices between $0.10 and $1.


3. Micro Coin: Extremely low-value coins with prices less than $0.0001.


4. Retrogressive Coin: Stablecoins with relatively stable prices.
5.

Never forget these that is how I am able to spot the growth and volatility. I am not an expert just some experience.

OpenAi bought Openclaw for autopilot workers agentic AI soon to carry many tasks at once .

I am working on an AI project called AI VPU (virtual processing Unit).

Validating African tech is crucial for global recognition . Let's celebrate and amplify homegrown innovations rather than criticism. Tell them about constructive improvement the whites will hardly validate African tech unless we are giving something in return.

megawealth01:
Explain

I was talking about US government shutdown

Bluearrow:
The only reason Bitcoinn may not get to 30k bottom is because everyone is predicting it online, go to Facebook, twitter, YouTube everyone is saying bottom is 30k & Bitcoinn like doing the opposite. Same way they were predicting 150 - 200k to top, but topped at 126k. Bitcoinn always like cutting short people expectations. If u have funds start buying only Bitcoinn gradually, it may disappoint everyone & not go below 50k.

150k is what we are expecting this year ending or early 2027 . The fact that crypto is heavily regulated is affecting trades and market sentiment is off the chart .

Looking at the funding level you will observe that BTC is flat like last week price , but alts are shaking things up. Prices are moving, and traders are getting opportunities to stack more . This is just another speculation make your analysis based on historical data.

We are lucky it is a partial shutdown today the market should have been bad .

Neurophos, an Austin, Texas-based startup, is pioneering photonic AI chips using metamaterial optical modulators to enable ultra-efficient optical computation. Founded as a spinout from Duke University research into metasurfaces (originally for applications like invisibility cloaks), the company has shifted focus to computing, developing an Optical Processing Unit (OPU)that performs matrix multiplications directly in light—bypassing traditional silicon limitations. A single Neurophos unit hitting 1.2 million tera operations per second would be a massive leap in compute power.


Unlike electron-based chips, which face resistance, capacitance charging, and heat from metal wires capping speeds at a few GHz, Neurophos' photonic approach uses light for operations at the speed of light with no such bottlenecks. Their metamaterial-based modulators are up to 10,000 times smaller than conventional optical devices, allowing millions to pack onto a chip. Each tiny cell multiplies input light by reflectivity, performing analog multiplication in physics; parallel across the surface, this creates a dense, high-speed optical matrix multiplier.

Performance claims are striking: a single chip targets 235 Peta Operations Per Second (POPS) at 675 W (around 348 TOPS/W), compared to NVIDIA's Blackwell GPU at roughly 9 POPS per 1,000 W (~9 TOPS/W)—offering about 30–39 times better efficiency. Scaling up, eight units could exceed a full GPU rack's performance with far less energy, potentially reaching exaOPS-scale systems. Throughput improves with larger area, flipping traditional scaling constraints.

Backed by heavyweights—including a $110 million Series A (2026) led by Gates Frontier (Bill Gates), with Microsoft's M12, MetaVC Partners, Aramco Ventures, Bosch, and others (total funding ~$118M)—investors see this as a way to overcome silicon's physical walls and sustain AI scaling into the late 2020s. Targeting hyperscalers for inference workloads (where efficiency trumps peak speed), Neurophos aims to transform data center economics by reducing power as the main bottleneck.

This could democratize AI access and accelerate growth—but it raises ethical questions: by removing energy constraints, does it unleash unchecked AI expansion amid widespread concerns? First evaluations start in 2026, with production targeted for 2028.

This is a major breakthrough low latency laser is another solution but it produces heat GPU heat up . Similar architecture just making a rack on a single unit traditional GPU would become obsolete .

megawealth01:
Are we doing lower?

52k soon dump hard. It is planned February 14 would be worse prepare .

Alphabyte3:
Reinforcement learning as a service RLaas in robotics. We need to improve on computing power to do this but offline and online services.

Robotics unsupervised learning uses algorithms to analyze raw data, finding hidden patterns or anomalies without predefined rules. It uncovers structures in unlabeled datasets. All robots developed is pre-trained to adapt it would be better in future doing tasks it isn't taught.


We need Nvidia,Unitree , Intel and Tesla to work on unsupervised learning rather than only supervised learning by increasing compute . This is a continuation of this idea