Scholarly Analysis: Ethiopia’s Draft Regulation on University Funding Autonomy and Performance-Based Block Grants – Implications for Higher Education Reform, Societal Returns, and the 2020 AAU Revitalization Recommendations.
Introduction
Birr Metrics (24 March 2026) reports a significant policy development in Ethiopian higher education financing: a draft Council of Ministers regulation that, for the first time, permits public universities to retain and roll over unspent state funds while transitioning to a performance-driven block-grant model. This reform replaces the longstanding “use-it-or-lose-it” line-item budgeting with a formula-based system weighted toward teaching costs, research output, technology transfer, innovation, and community engagement. Funding is structured in two streams—a general-purpose block grant covering up to 40 percent of core operations, supplemented by performance-linked allocations and targeted support for national priorities (infrastructure, teaching hospitals, inclusion)—coupled with mandatory performance contracts, quarterly reporting, audits, and oversight by a new Block Grant Management Council involving the Ministries of Finance and Planning and Development. The changes are slated for implementation in the current fiscal year upon final approval.
This announcement directly operationalizes long-standing calls for institutional autonomy and outcome-oriented governance. It is particularly salient in light of the “Addis Ababa University Revitalization Study Committee Report” (July 2020), to which I contributed as a committee member alongside other Ethiopian and a diaspora scholar. That report was submitted to then-Minister-to-be Berhanu Nega and the AAU Board of Trustees at a time when the flagship university—and the broader public higher-education system—faced chronic underfunding, politicized decision-making, programmatic fragmentation, and weak alignment with national development needs. The committee’s diagnosis and four-pillar recommendations (restored autonomy via charter and shared governance; diversified, performance-oriented funding; programmatic differentiation; and strengthened research-society linkages) provide a rigorous analytical lens through which to evaluate the 2026 draft regulation.
Background
Higher education in Ethiopia has long been viewed as a strategic public good essential to nation-building, human capital formation, and socio-economic transformation. Successive governments have invested heavily in expansion—public universities grew from two in the early 2000s to over 45 by the mid-2020s, with enrollment surging from roughly 10,000 to over 800,000—yet persistent challenges of quality erosion, politicization, resource fragmentation, and misalignment with labor-market and societal needs have undermined returns on this investment. The 2020 “Addis Ababa University Revitalization Study Committee Report” (hereafter the “2020 Report”), to which the author of this query contributed as a committee member, offered a rigorous, evidence-based diagnosis and reform blueprint precisely to address these deficits at Ethiopia’s flagship institution. Submitted in July 2020 to the AAU Governing Board (and indirectly informing the Ministry of Science and Higher Education), “…the Report was prepared by an eight-member committee that included Prof. Teshome Abebe alongside distinguished Ethiopian and diaspora scholars”.
The Report’s core diagnosis was that AAU—and by extension much of Ethiopian public higher education—suffered from systemic loss of institutional autonomy, chronic underfunding relative to mandates, politicized governance, fragmented research, and programmatic overstretch (“trying to be all things to all people”). These factors produced graduates lacking practical skills, weak societal linkages, and inefficient resource use. The committee’s recommendations centered on four interlocking pillars: (1) restored legal and operational autonomy via a charter and shared governance; (2) diversified, performance-oriented funding combining stable government block grants with internal revenue generation (contract research, endowments, tuition/fee contributions, and enterprises); (3) programmatic restructuring and differentiation to concentrate resources on high-impact areas aligned with national priorities; and (4) strengthened research-community linkages to enhance societal relevance.
Ethiopia’s current higher-education reforms—led by Minister of Education Prof. Berhanu Nega and operationalized through the “Universities Autonomy Proclamation No. 1294/2023”, performance-based contracts (rolled out since 2024), formula-based budgeting, institutional specialization, and program consolidation—represent a partial but significant realization of the 2020 vision. These measures shift from input-driven, enrollment-maximizing line-item budgeting to outcome-linked, autonomous, and differentiated funding. Public universities now sign annual performance contracts with the Ministry, with funding tied to measurable indicators (research output, graduate quality/employability, and contribution to national development). Institutions gain control over rolled-over funds, while low-enrollment or non-specialized programs face consolidation (147 programs merged into 54) or repurposing. Students increasingly choose universities, and unselected institutions may be redirected toward alternative missions (e.g., TVET or regional service hubs).
Education and Society’s Interest in Ethiopia
Ethiopian society has a profound stake in higher education as a driver of inclusive growth, civic cohesion, and technological sovereignty. With a youthful population (median age ~19) and ambitions under the Ten-Year Development Plan, the sector must produce not merely credentials, but problem-solvers equipped for agriculture modernization, industrialization, digital transformation, and peace-building. The 2020 Report explicitly framed AAU’s revitalization as a national imperative: a research-intensive flagship that could model excellence, generate policy-relevant knowledge, and inculcate critical thinking and ethical citizenship. It warned that continued mediocrity risked “brain drain, sub-standard graduates, and irrelevance to Ethiopia’s development.”
The new approach aligns with this societal interest by prioritizing “quality and relevance” over undifferentiated expansion. Specialization—assigning universities missions based on geographic strengths (e.g., agro-processing in agrarian zones, engineering in industrial corridors)—directly echoes the Report’s call to “streamline programs and free up resources” to avoid “diploma mills”.
Performance contracts and formula funding incentivize alignment with labor-market signals and national priorities, potentially raising graduate employability and research uptake. Autonomy provisions in Proclamation 1294/2023 enable universities to mobilize private resources and respond nimbly to societal needs, reducing the historical politicization that the 2020 committee identified as corrosive to academic freedom and meritocracy.
Advantages of the New Approach
From a policy and academic standpoint, the reforms offer several rigorously defensible advantages that address the 2020 diagnosis head-on:
1. Efficiency and Fiscal Sustainability: Formula-based and performance-linked funding replace opaque line-item allocations with transparent, incentive-compatible mechanisms. Universities can retain and reinvest surpluses, mirroring the Report’s advocacy for internal revenue generation (e.g., Makerere University’s model, which achieved >30% self-financing). This reduces fiscal pressure on the federal budget (historically >40% of education spending on higher education) while encouraging cost discipline.
2. Quality and Differentiation: Program consolidation and specialization counter the “multiplicity of programs diluting quality” flagged in 2020. By concentrating expertise, universities can invest in labs, faculty development, and interdisciplinary research—directly supporting the Report’s recommendations for thematic, stakeholder-aligned research and restoration of general-education competencies. Early evidence suggests contraction in enrollment is forcing a shift from quantity to quality, with performance contracts emphasizing research contributions and student outcomes.
3. Governance and Autonomy Gains: Proclamation 1294/2023 and performance contracts operationalize the 2020 call for a charter, shared governance, and reduced ministerial micromanagement. Merit-based leadership, decentralized decision-making, and academic freedom provisions should mitigate the “top-heavy,” politicized structures criticized in the Report.
4. Societal Return on Investment: Specialization tied to regional strengths and national development goals (e.g., via performance indicators) enhances relevance, fulfilling the Report’s vision of universities as “unifying forces” that study societal cultures/values and forge industry linkages. This could accelerate innovation diffusion and reduce graduate unemployment and underemployment.
Potential Consequences for University Funding.
While promising, the transition carries risks that policymakers and academics must monitor and mitigate—risks the 2020 committee implicitly anticipated when stressing “sustained funding” alongside autonomy.
– Access and Equity Trade-offs: Reduced enrollment and program closures may disproportionately affect students from under-resourced regions or lower-performing secondary schools. If performance contracts penalize institutions serving disadvantaged populations, geographic and socio-economic disparities could widen. The 2020 Report warned against “regimentation” in admissions; safeguards (e.g., targeted scholarships, remedial pathways) are essential to preserve equity commitments central to Ethiopian higher-education policy.
– Short-Term Funding Volatility and Institutional Stress: Performance-based models reward high performers but may starve under-resourced or transitionally weak universities. Formula funding assumes reliable data and fair metrics; poor design could exacerbate brain drain or faculty disengagement—the very issues the Report diagnosed. Rollover control helps, but without transitional support (e.g., capacity-building grants), some institutions risk operational collapse or downgrading.
– Implementation and Political Economy Risks: Autonomy is qualified by “national interests”; residual ministerial influence or inconsistent regional application could undermine gains. Faculty morale may suffer if workload increases without salary reform or research incentives. The Report emphasized competitive remuneration and internal revenue sharing; without these, performance contracts risk becoming punitive rather than developmental.
– Longer-Term Societal Impacts: A leaner, higher-quality system may better serve Ethiopia’s knowledge economy, but rapid contraction could temporarily reduce human-capital pipelines in critical sectors. If specialization overlooks interdisciplinary or liberal-arts needs, broader societal capacities (civic literacy, cultural preservation) may suffer—contrary to the 2020 emphasis on balanced general education.
Policy Implications and Forward Path
The current reforms constitute a pragmatic, if belated and imperfect, implementation of the 2020 committee’s scholarly recommendations. They move Ethiopian higher education from a politicized, input-heavy model toward an autonomous, performance-driven, differentiated system better suited to 21st-century development challenges. For academics, the reforms open avenues for rigorous impact evaluation—longitudinal studies on graduate outcomes, research productivity, and equity metrics are urgently needed. For policymakers, success hinges on three complementary actions: (1) ring-fenced transitional funding and capacity support; (2) transparent, stakeholder-validated performance metrics; and (3) complementary investments in secondary education and TVET to maintain access pipelines.
As a participant in the 2020 process, I note that the committee foresaw precisely this tension between fiscal realism and societal aspiration. The new approach’s emphasis on autonomy, specialization, and performance accountability validates the Report’s diagnosis while testing its prescriptions in practice. Ethiopia’s society stands to gain substantially if implementation remains evidence-based, inclusive, and adaptive—transforming universities from mass producers of credentials into engines of innovation, equity, and national cohesion. Continued dialogue between the academy, government, and civil society will be vital to refine the model and safeguard its developmental promise.
Teshome Abebe, PH.D., A former Provost and Vice President for Academic Affairs, is Professor of Economics and Faculty Laureate.
Editor’s Note : Views in the article do not necessarily reflect the views of borkena.com
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Professor, I like many others who read your writings with great interest and appreciation for time in doing so, and its great to learn (in this article) that you are far more involved than just posting your ideas here on this medium.
However, something huge has happened between December 2025 and March 2026 that has the potential to change everything we have known about knowledge in general, and specifically its application in the job market and the changing workplace, not only in the near future (3, 6, 12 months… ) but today, at-least in the ‘developed world’ even in the heart of ‘silicon valley’ where software-engineers are becoming the ‘weakest-link’ in the development-space and are forced to strap a head set to give verbal instructions (‘PROMPTS’) to the AI that is becoming way better than and FASTER than the very top in the field (their typing is slowing development).
Their challenge is to abandon what they have been good at doing and successful for decades, and have to LEARN to summarize the task of developing an application into a single paragraph using simple spoken-English just like a kid learning to write A,B,C,Ds while doing so, in the back of their mind (knowing how fast good AI has become) they hear a distant sound of a printer processing their last ‘pay cheque’ in the very distant/ near future, for those that are not ‘partner’ with the firm.
It is hard to say the phenomenon observed in the West now correlates with the idea and place discussed in the article, however the ‘trickle down effect’ is unavoidable, for the time horizon of the policy discussed. the quick nature of AI influence spreading to the ‘developing nations’, educational environment. And weather Universities are or remain to be the place for AI lead learning ( if ‘learning’ is even the right TERM) when the scientists who TRAINED AI till 6 months or less ago are no longer needed since AI is learning by itself at higher speed rate making the humans the ‘weakest-link-in-the -chain’, and those scientists find themselves in awkward situation, and realized their next role is if they want to be relevant is to ‘learn’ how to compose effective AI ‘instructions’ (PROMPTS’) (the new way of communication with) for AI to do something/anything, for them, going forward.
Here is one of the Top ‘machine-learning’ expert for the last 3 decades explaining what just happened in the last 2 months and half.
” Andrej Karpathy on Code Agents, AutoResearch, and the Loopy Era of AI’
link = youtube.com/watch?v=kwSVtQ7dziU
Ethiopian Job market for University graduates:
————————————————————–
Here is a result of a quick search/AI find for a question ‘ How many Ethiopia university gradates get employment opportunity in 2025?”:
AI Assist:
‘In 2025, the employment opportunities for Ethiopian university graduates are expected to remain challenging, with many facing difficulties in securing jobs due to a disconnect between academic training and labor market needs. The situation is exacerbated by high competition among graduates, particularly in fields like engineering, where unemployment rates are notably high.’
–> Followup question: “how was in 2024?”
AI Assist:
‘In 2024, Ethiopia’s labour market remained challenging for university graduates:
– Official overall unemployment was low (~3.3–3.4% in 2024, ILO/World Bank modeled estimates), but graduate-specific unemployment studies and labour‑market profiles (2024) show a persistent mismatch between higher education supply and formal job demand — resulting in higher unemployment and underemployment among degree holders than the national average.
– Key factors cited in 2024 analyses: rapid expansion of higher education without commensurate quality/skills alignment, limited formal-sector job growth, high informality, and regional/urban disparities (urban graduate unemployment much higher than rural averages).
– Policy responses noted in 2024: job‑creation plans (e.g., Ethiopia’s Plan of Action for Job Creation 2020–25), emphasis on entrepreneurship and private‑sector engagement, and targeted programmes (including ILO/partner interventions) to boost skills and formal employment.
If you want specific numbers for “graduate unemployment rate in 2024” or sources (CSA/ILO/World Bank/2024 labour market profile), I can fetch and cite the latest reports.’
–> Followup: “Yes, please do”
AI Assist:
” Key 2024 figures (graduate / youth-focused)
————————————————————
– **Youth unemployment (15–24)**: ~6.0–7.0% in 2024 (modelled ILO/World Bank ranges); urban youth rates higher (double digits in some urban centres).
– **Young graduates / tertiary-educated unemployment**: Multiple 2023–2024 labour‑market profiles and studies report that unemployment among tertiary-educated/job-seeking graduates is substantially above the national average — commonly cited in the **10–20% range** for unemployment or open joblessness, with larger shares facing underemployment or working in informal/low‑skill jobs. Precise point estimates vary by data source and definition (recent graduates vs. all tertiary-educated).
– **Overall national unemployment (all ages)**: ~3.3–3.4% in 2024 (World Bank / ILO modeled estimates), which understates graduate/job-seeker difficulties because most graduates compete for formal/urban jobs.
– **Informality and underemployment**: A large share (>50%) of employed graduates work in informal or subsistence activities or are underemployed (working below qualification level), according to sectoral and policy reports from 2023–2024.
Context and drivers noted in 2024 reports
———————————————————
– Rapid expansion of tertiary enrolment outpacing formal-sector job creation.
– Skills mismatch between university curricula and employer needs (technical, digital, soft skills).
– Weak private‑sector absorption and slow formal job creation.
– Regional disparities and impacts from conflict and economic shocks increasing barriers in affected areas.
Representative 2023–2024 sources (to consult for exact point estimates by year/age/education)
———————————————————————————————————————————–
– International Labour Organization — Ethiopia country labour market profiles / youth employment briefs (2023–2024).
– World Bank — Ethiopia economic updates and labor statistics (2023–2024).
– Ethiopia Central Statistical Agency (CSA) — Labour Force Survey publications (most recent rounds covering 2022–2024 indicators).
– Government of Ethiopia — Plan of Action for Job Creation 2020–25 and related monitoring briefs.
– ILO / UNICEF / UN reports on youth employment and skills (country briefs 2023–2024).
If you want, I can fetch specific numeric tables and direct report links (CSA Labour Force Survey figures for 2024, ILO youth unemployment by education, and World Bank modeled estimates) and list the exact citations and quoted unemployment percentages. Which set of documents should I pull first: CSA (national survey) or ILO/World Bank (modelled comparable youth/graduate rates)?’
AI assist:
summary:
=======
‘In 2024 Ethiopian university graduates faced substantially tougher labour-market outcomes than the national average. While overall unemployment was low (~3.3–3.4% from World Bank/ILO modelled estimates), studies and labour‑market profiles from 2023–2024 show tertiary‑educated and recent graduates experience much higher open unemployment—commonly reported in the 10–20% range—and large rates of underemployment and informal, low‑skill work.
Key drivers cited were rapid expansion of higher education without matching quality or employer‑relevant skills, weak private‑sector formal job creation, urban–rural and regional disparities, and economic shocks/conflict that depressed opportunities in affected areas. Policy responses in 2024 emphasized entrepreneurship, skills realignment with employers, and job‑creation programmes under Ethiopia’s Plan of Action for Job Creation 2020–25, but implementation and private‑sector absorption remained constrained.’
The recent university graduate unemployment rate is not unique to Ethiopia. In the US according to the stats shown in the podcast below and the number of graduates that were able to get employment & the pay has gone down gradually for the last 5 years, and in 2025 only 19% got jobs with ~20-25% less pay compared to 4-5 years earlier.
‘Moonshots’
Peter H. Diamandis, March 20/26
Link = youtube.com/watch?v=uOGHXAfvK8w
New one released today ( I have not watched it yet ), would be interesting & informative as usual..
Link = youtube.com/watch?v=wMLcIWLlcWg
The “2020 committee’s scholarly recommendations.”
First of all it is 6 years old, and let us say it may have helped in some ways or have been looked at and or discussed, but as the world of learning and work turned upside down with what transpired in the last 3 months of 2026, a totally NEW approach needs to be devised.
What worked in the last century, no longer is applicable in the 21st century, especially after what emerged in March 2026, that shocked even the very experts that helped develop AL. The old-ways-are-over! Universities will go empty sooner than we think, and the job opportunities for those kind that are coming out end of 2026 in the West is going to be bad, Let alone to encourage those finishing high school to university is going to be job-security for the academicians but the kids. When the days of memorizing theory slowly is coming to an end, even there AI can explain any given theory/concept to a 5 year old to a teenager, to an undergrad, and to PhD level, in a very simpler and age & level appropriate ways than any human ‘expert’-educator can 100% hands down.
Here is a excerpt from a newsletter i got this morning… (I will post the link at the bottom…)
“What You Need to Do
=================
Okay, so the machine is building itself. Recursive self-improvement has escaped software. AI is designing chips, building fabs, and launching models anonymously. What do you do about it?
If you’re an entrepreneur:
———————————
Stop competing on generic software features. Start accumulating proprietary data in your domain. The models are becoming commodities, your data isn’t. Find the bottleneck in your industry and build the vertical integration to iterate faster than anyone else. Elon’s showing you the playbook: don’t wait for suppliers to catch up. Build it yourself.
If you’re a student:
————————-
Replay Alex Wissner-Gross’ explanation of distillation ten times until you fully understand it. Then ask your favorite AI to generalize on it and find every document you can around the internet to read. At the end of that process, you’ll be able to build a distilled, focused model that solves some problem better than anyone else on the planet. That’s instant value. That’s instant employability. That’s your ticket to the future.
If you’re a parent:
————————
Your kids need to understand that the future belongs to people who can leverage AI, not compete with it. The engineers aren’t going away. In fact, they’re being multiplied. But the ones who thrive will be the ones who use AI to design ten chips instead of one. Teach your kids to think in terms of leveraging superintelligence, not fighting it.
If you’re an investor:
————————–
Look for the innermost loop. Alex has been beating this drum for months, and he’s right. The tailwinds in equities and assets are like nothing we’ve ever seen, but you have to be in the AI loop to be relevant. Go to 13f.info, look up Leopold Aschenbrenner’s Situational Awareness Fund, and study his holdings. He’s buying chip fabs, power infrastructure, chip design companies, algorithmic plays: anything directly in the centerpiece of the innermost loop. That’s your roadmap.
Here’s my final thought:
=================
The singularity isn’t waiting. The machine is building itself right now: faster than most people realize, faster than most institutions can adapt.
We’re watching the loop close in real time. AI designing chips. Those chips powering better AI. That better AI designing better chips. And the cycle accelerates.
The question is not whether this is happening. The question is whether you’re positioned to benefit from it or be disrupted by it.
Choose wisely. The future is being built this week.
— Peter”
link = metatrends.substack.com/p/the-machine-is-building-itself?utm_campaign=email-half-post&r=3y4yp9&utm_source=substack&utm_medium=email
When the personal computer was introduced, job loos was predicted… but more jobs were cleared afterwards, but when cellphones became available to everyone since 2007, the old land-line no longer part of the residential homes building requirements replaced by network-outlets, even old homes with land-lines are rarely used. Days of universities becoming like the land-lines is not far.
AI on the cellphone can answer any equation when told who is the level of age group & educational level & language of recipient, traditional schools gradually become a babysitting-place for children under 14… and a robotic AI can teach students from grade one to any level all in one room and advise graduate students any level at the same time in all major languages in its dataset.
We are emerging into a new world. And the advise and guidance given or about to be given needs to be all encompassing and timely or ahead of the time we live in, and what is LIKELY to come in the TIME-HORIZON.
Be well.
Happenings: AI Agents replacing workers… in real time.
—————————————————————————-
“How I Replaced My Entire Marketing Team With 7 Agents’
Link = youtube.com/watch?v=THx8X6anPPg
For those who want to get frequent updates on AI development & daily (New) events… here are a few links…in addition to the above, daily AI related updates sites. There are many… (‘how to’ sites) but these 3 are a good starting place..
1) theneurondaily.com/ ( Daily newsletter)
2) /metatrends.substack.com/ ‘”
3) Moonshots ( a biweekly podcast on YT)
Be well.
#4)
AI – ROBOTIC development NEWS – frequent update source
Link = youtube.com/watch?v=uV2qLhnc85k
Be well.
The huge ‘CHANGE’ I mentioned between Dec 2025 – March 2026 ( the first 75 days of 2026) in my comment is called “OpenClaw”, it is an application (not an AI) that simplified/changed /automated how AI Large Language Models (LLMs) are going to be used /accessed. Think of it this way, the LLMs are huge Libraries with no librarian up to early 2026, and here came a small team put together Opnecalw to be a Librarian to any LLM people /companies use, and that librarian can manage many Agents with specific skill sets to complete requests that come forward and assigned to them, and report back to the librarian who is going to inform the CEO the human the job is complete.
Which means the CEO or his VPs spend a few minutes to compose a few lines of instructions ( PROMPTS) to the Librarian, and do other things with the rest of the day. That is huge! Simply because the CEO & VPs can only work for a certain amount of hours a day, but the Librarian and his specialized-helpers/experts work 24/7, 365.
“OpenClaw Architecture, Explained”
==========================
Link = ppaolo.substack.com/p/openclaw-system-architecture-overview
OpenCalw own site: with a lot on information and “Quick start’ command code.
link = openclaw.ai/
Video explanation:
————————–
Her is the best explanation and how to set it up in minutes… with lots of gems!
( though he picked a commercial LLM, OpenClaw works with all LLMs including the Opensource from China (most businesses in the West are using to cut COST).
“OpenClaw……RIGHT NOW??? (it’s not what you think)”
Link = youtube.com/watch?v=T-HZHO_PQPY
Lot of examples & Command code hints… very useful for students to dig deeper and see what is under the hood.
He is looking to continue with this series, to expand on the use-case and more. So keep an eye on it…
Be well.
And finally:
“Prompt engineering’: A – Z , LLMs, introduction to Agents, Agent workflow, Context engineering, generating code, papers, tools, datasets, services… and many more, all in one place…
Link = promptingguide.ai/
–> Make sure to look into Andrej Karpathy’s “AutoResearch”, a very powerful tool. (just google it)
Sorry for the spam… (wasn’t organized to put them all in one… (ideas coming late))
Be well
Here is a very cost effective way to implement Digital learning (AI) in rural Ethiopia
Solar panel, local Opensource Large language Models (LLMs) on single machine and AI could tech Math, Language, Science, in the language they understand some LLMs come with 140+ languages… with local teachers guiding & assisting the process.
Chinese Huawei Solar based Digital Schools in rural Nigeria and Brazil shown at Spain’s Tech show 2026.
@1:09
Link = youtube.com/watch?v=AeHFiJuSE20
Going forward what is needed in the nations Education system is not MEMORIZING, but teaching kids ‘critical thinking’ & developing IDEAS and GIVING IT to AI to research, analyze, and produce the intended RESULTS or PRODUCT prototype /Service models.
AI has the DATA ( the collective data of humanity, all that has been documented) it CANNOT create NEW Ideas, NEW IDEAS come from PEOPLE, so what we need to teach is not what AI already can deliver INSTANTLY, the Students to DEVELOP ‘critical thinking’ and formulating IDEAS and test their ideas by giving it to AI via PROMPTS.
The material presented in ‘PROMPTS ENGINEERING’ at link = promptingguide.ai/ should be portioned out in AGE specific format and PRINTED out as schools curriculum AI learning BOOKS and designated as school text and provided in print as well as digital format across the country, for the coming school year.
This move not only prepares the next generation to the (new) 4th industrial revolution, but is a game changer today for the nation’s economic development path as whole.
Be well.
‘Googles Gemma 4 Just Shocked The AI Industry’
140 + languages
Runs on Cellphone, Laptop, desktop, all for FREE
Link = youtube.com/watch?v=W9zZ5r2C5YE
Be well.
‘The Skynet Moment: How Mythos AI Just Changed Cybersecurity Forever – And Why It Should Scare You’
———————————————————————————————————————————————–
Link =youtube.com/watch?v=X_4rKVXev8k
#2
‘Mythos is about to CRASH the markets’
——————————————————
“I found more about ‘bugs’ ( ‘vulnerabilities’, in software) in the last couple of weeks than I found in the rest of life combined”, Software security specialist..
This is happening in only the first 3 months of 2026, there are 9 more months to go before we turn the page to 2027; by then what was known for the last ~100,000 years would amount to basically to NOTHING ( but all we know well is kill each other, not knowing the whole thing/system is ONE, but appearing as many… “Appearances are deceiving.”…
Link = youtube.com/watch?v=r4JGNJfNQeA
Some alien species before us, such as the ‘Grays’ were so much mesmerized by AI they chose their race to be transformed (DNA engineered) into AI based ( they did not do it themselves, but by their colonizers the Reptilian race from Alpha Draconis system (‘allegedly’, who are here among us)) as a result they could not ‘reproduce’ among themselves so to preserve their species, they ‘abduct’ (collaborate) with other species to co-create a 3rd species…
Some among us are already implanting chips to avoid carrying they wallet or office/home keys (could it be the Rs to convince us ?) , nonetheless a split is already in stage one…
search.brave.com/search?q=the+ufo+entities+such+as+reptilians+and+all+theothert+slist&source=web&summary=1&conversation=08f3f1bc5e7cf94234735c0f60952d77a58c
And the rest of us are heading the Jesus way, following his foot steps to awaken the ‘Creator-within’ (activating some of thee ‘junk’ DNA) each-one of us carry; knowing full well AI is just a TOOL to be USED, nothing more.
So, EDUCATION in the current fast-changing environment should FOCUS on teaching kids READING & WRITING , and CRITICAL THINKING as to how to ask better questions (PROMPTS) AI tools, or ask AI tools to create a better question for us based on our own ideas…
Our ‘trupm-card’ (no pun intended) is our 12 strands of DNA ( of which only 2 are activated, to help us eat sleep and multiply without the need to managing all the human-systems…) that separates us from all the rest of thee species that exist in the lower 3 & 4 dimensions (book of Henoch, ‘ his visits to such places ‘ ) …
Be well.