randolph odekhe

[Omoyele Sowore @sowore]

GANG OF THIEVES: The IMF has revealed that @officialABAT and his gang of thieves cannot properly account for public spending worth about 2% of Nigeria’s entire GDP, roughly ₦8.8 TRILLION.

Off-budget spending, hidden from proper scrutiny and accountability. This is not a government; it is an organized looting operation! #RevolutionNow #Sowore2027

[Peter Obi @PeterObi]

Grand Corruption: Nigeria’s Greatest Threat.

The recent report from the IMF consultation further raises concerns about the scale of grand corruption under the Tinubu government. The IMF now reveals that about N8.83 trillion in expenditure undertaken in 2025 is not reflected in the budget. This expenditure is not budgeted and is therefore not under legislative oversight or administrative scrutiny. This is horrible.

N8.83 trillion is as follows:

1.About 2% of our GDP.

2.Over 35% of Nigeria’s 2025 N23.96 trillion capital project budget. In fact, the amount is more than the actual released capital funding for 2025.

https://t.co/Hta3LViCB8 is more than the entire combined budget for education (N3.52 trillion) and health (N2.38 trillion).

If such an amount is properly used and accounted for, it could transform Nigeria’s public health and education sectors. It could create hundreds of cottage industries that can provide jobs for thousands of graduates and build a solid foundation for economic development. But we cannot account for it. This is not an isolated incident.

This is a pattern of grand corruption that has become part of this administration.
We have a lot to worry about regarding the state of corruption under President Tinubu. The sort of corruption that is ingrained in total disregard of elementary rules of public finance management poses a grave danger to national security and the stability of the Nigerian state. The capture of the Nigerian state and the plunder of its resources are actions that undermine the basis of state stability and deepen poverty and state failure.

This recent revelation proves that the APC government is grossly corrupt, incompetent, and insensitive. With the growing poverty and the urgent need for significant upgrades to social and physical infrastructure, a responsible and responsive government would ensure that N8.83 trillion is prudently utilised to address these gaps. But not the Tinubu administration.

A few days ago, I called on President Tinubu to resign from office for incompetence, lack of capacity, lack of compassion, and failure to improve on his campaign promises. Some people thought perhaps the call was excessive. But with the daily revelations of pervasive corruption in this administration and its total lack of commitment to the welfare and security of Nigerian citizens, the only reasonable action is for President Tinubu to resign from office. The collapse of elementary forms of due process under Tinubu and the increased evidence of rampant looting of Nigerian public finances reinforce the need for greater accountability. It is now time for Nigerian citizens to rise within the law and hold this administration to account.

A New Nigeria is POssible. -PO

[randolph odekhe @randolphodekhe]

@bullbearalpha @elonmusk @SawyerMerritt you are wrong, without the gpu, what do you need to power, cool and so on.

[Uzair @uzair_dev_]

What type of developer are you?

- Frontend
- Backend
- Full stack
- DevOps

[Python Programming @PythonPr]

Layers of AI

[Vivo @vivoplt]

Don’t overcomplicate it.

• Build a Password Manager to learn file handling, hashing (not full crypto)
• Build a URL Shortener to understand routing, IDs, and persistence
• Build a Todo App with deadlines to practice CRUD and basic state
• Build a Web Scraper to learn requests, parsing, and rate limits
• Build a CLI Expense Tracker to master logic, files, and edge cases
• Build a Log Analyzer to work with files, timestamps, and patterns
• Build a Simple Recommender using similarity rules (not ML magic)
• Build an Email Automation Script using SMTP and scheduling

Projects. Not tutorials.

[Smart👨‍💻 | Software Engineer @smartnakamoura]

If you are a software engineer who wants to upskill in system design, bookmark these 10 sites:

[𝘼𝙡𝙚𝙭 @ItsAlexhere0]

Top Tech YouTube Channels to Follow in 2026

1. AI – Yannic Kilcher
2. Cloud – Google Cloud Tech
3. Security – LiveOverflow
4. Frontend – The Net Ninja
5. Python – Corey Schafer
6. DevOps – Nana
7. Data – Luke Barousse
8. Databases – CMU Database Group
9. System Design – Gaurav Sen
10. Linux – Learn Linux TV
11. Networking – David Bombal
12. Math – 3Blue1Brown
13.C++ – The Cherno
14. Software Dev – Fireship

Bookmark this list.

[Vaishnavi @_vmlops]

This is actually crazy 🤯

https://t.co/yReuA8ki65

A whole job hunting system built like a DevOps pipeline… tracking apps, tailoring resumes, everything automated

CI/CD for getting hired?? yeah we’re living in the future

[Alex Xu @alexxubyte]

Top 12 GitHub AI Repositories

These repositories were selected based on their overall popularity and GitHub stars.

[Giuliano Liguori @ingliguori]

8 specialized AI model types 👇

LLM → text generation
LCM → semantic reasoning
LAM → action-oriented agents
MoE → expert routing
VLM → vision + language
SLM → lightweight edge models
MLM → masked token learning
SAM → image segmentation

AI is moving from “one big model”
to specialized architectures.

#AI #LLM #MoE #VLM #MachineLearning

[Zain Kahn @heykahn]

Before you spend $2,000 on an AI course, read this.

A lot of people are buying expensive AI courses right now.
But honestly, most of them don’t need to.

Some of the best AI learning resources in the world are already free. And they’re not built by self-proclaimed AI experts online.They’re created by the companies actually building the models, chips, tools, and infrastructure behind this entire AI wave.

If you want to learn AI properly, it makes sense to learn directly from the source.

But before that, Check out 100+ such resources shared in this community of 200K+ AI/ML Engineers: https://t.co/1551GLLSyi

Here's a list of 10 free AI learning platforms from industry leaders:

𝟭 - 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰:
https://t.co/i11SbYMwsc

𝟮 - 𝗚𝗼𝗼𝗴𝗹𝗲:
https://t.co/AP7UJIWCZS

𝟯 - 𝗠𝗲𝘁𝗮:
https://t.co/Szgt9UZwEG

𝟰 - 𝗡𝗩𝗜𝗗𝗜𝗔:
https://t.co/jhKE77g8qA (GOATed)

𝟱 - 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁:
https://t.co/7oyuGNBso1

𝟲 - 𝗢𝗽𝗲𝗻𝗔𝗜:
https://t.co/SB5qSuOJND

𝟳 - 𝗜𝗕𝗠:
https://t.co/bivomoOsgU

𝟴 - 𝗔𝗪𝗦:
https://t.co/4XySMsxNbR

𝟵 - 𝗗𝗲𝗲𝗽𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴𝗔𝗜:
https://t.co/wW9udDmT29

𝟭𝟬 - 𝗛𝘂𝗴𝗴𝗶𝗻𝗴 𝗙𝗮𝗰𝗲:
https://t.co/9llzeMmuAo

If you’re serious about learning AI, the biggest difference usually comes from consistency, not another course.

[Mohini Shewale @s_mohinii]

🚨𝗕𝗥𝗘𝗔𝗞𝗜𝗡𝗚: Build your next app without spending a dollar on data.

Someone made a list of 320,000+ free public APIs, and developers are going crazy.

→ Weather, finance, news, sports, crypto
→ AI & machine learning APIs you can call right now
→ Government open data, maps, geolocation
→ Entertainment: movies, music, games, anime
→ Categorized, searchable, and verified as working

Free and 100% open source. Link Bellow:👇 just like + comment " send" + repost+ Follow me so that it can be auto DM.

[Ifeoma C. N @__iffff]

Not a bad way to design your wardrobe storage.

[Health & Living @HEALTH__LIVING]

Full body workout 🔥💪

[Khushabu Agrawal @khushabu_27]

FREE Data Science Courses w/ Certificates

❯ Python
https://t.co/vq2VMVnP91

❯ SQL
https://t.co/6A4Unvj2hy…

❯ Data Analysis
https://t.co/CSLIvjP8Nb…

❯ PowerBI
https://t.co/q6zRPmp1GS…

❯ Excel
https://t.co/0fSDVuhOma…

❯ Tableau
https://t.co/dIHyUe18EZ…

❯ R
https://t.co/gy0gC4YBae…

❯ Data Cleaning
https://t.co/1Izx08614W…

❯ Data Visualization
https://t.co/j2S1O2jlHi…

❯ Mathematics & Statistics
https://t.co/imgU0Ye7Ev

❯ Probability
https://t.co/gy0gC4YBae…

❯ Machine Learning
https://t.co/7blWGmBSb0…

❯ Deep Learning
https://t.co/gNNj1cdISd…

[Ronin @DeRonin_]

How to become AI engineer in next 6 months:

By the end, you want to be able to:

- build LLM apps end-to-end
- use APIs from OpenAI / Anthropic / open-source stacks
- design prompts and context properly
- add tool calling and structured outputs
- deploy real projects

So, let’s discuss your roadmap month by month

Month 1: Get solid enough in coding and fundamentals

What to learn:

- Python really well
- Git + GitHub
- CLI / terminal basics
- JSON, APIs, HTTP, async basics
- basic SQL
- basic data handling with pandas
- virtual environments, package management, error handling
- FastAPI or Flask

Month 2: Master LLM app development

What to learn:

- prompting fundamentals
- system vs user instructions
- structured outputs / JSON schemas
- function/tool calling
- streaming responses
- conversation state
- cost / latency / token basics
- failure handling
- prompt injection awareness

Month 3: Learn RAG properly

What to learn:

- embeddings
- chunking
- vector databases
- metadata filtering
- reranking
- retrieval quality issues
- hallucination reduction
- citations and grounding

Month 4: Agents, tools, workflows, evals

- agent loops
- tool selection
- state management
- retries
- when NOT to use agents
- multi-step workflows
- evaluation harnesses
- task success metrics

Month 5: Deployment, product thinking, and reliability

What to learn:

- FastAPI production patterns
- Docker
- background jobs
- queues
- auth + API key security
- logging
- observability
- prompt/version management
- eval dashboards
- cost monitoring
- rate limits
- caching

Month 6: Specialize and become hireable

these knowledge and skills you gained can be applied in three directions

you need to choose one of them and focus on practice

although everything mentioned above is also best learned purely through practice

Direction 1: AI product engineer

Best if you want startup jobs fast

Focus on:

- LLM apps
- RAG
- agents
- deployment
- product UX

Direction 2: Applied ML / LLM engineer

Focus on:

- fine-tuning
- when to fine-tune vs prompt
- evaluation
- inference optimization
- open-source models
- training pipelines

Direction 3: AI automation engineer

Focus on:

- workflow orchestration
- business process automation
- multi-tool systems
- CRM, docs, email, support, ops use cases

This roadmap will help you go through a practical path, and the key is to study each of these points and then test them in real work

By month six, you will already have several built products or examples of completed tasks

And it will be much easier to get a job as an AI engineer

Save it so you don't lose it and can return to study later

[Miles Deutscher @milesdeutscher]

CANCEL your weekend plans.

You NEED to:

• Learn Claude Code
• Learn Cowork (build 1-2 practical workflows)
• Set up Perplexity Computer/Perplexity Finance
• Optimise Cowork (plug-ins + skills)
• Set up OpenClaw
• Test Google AI products (Nano Banana 2, NotebookLM & more)
• Experiment with basic agentic solutions (Manus)
• Use AI to create a business plan/strategy/context files
• Build an AI second-brain database (Notion)
• Experiment with Notion Agents' *brand new*
• Learn basic automation tools (MCPs, Zapier, n8n)
• Learn prompt engineering - the better you can communicate with AI, the better your Outputs
• Read AI articles
• Dive into robotics
• Research AI stocks/ETFs/investment arbitrages

You have way too much to do...