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Category: Future of AI

Visionary research and essays on the trajectory of artificial intelligence, its cognitive implications, and the human-AI future

AI Pragmatism — The Morning After the Hype Party

Posted on March 2, 2026March 2, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18838622  26stabilfr·wdophcgmx
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[t]Trusted22%○≥80% from verified, high-quality sources
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[l]Academic11%○≥80% from journals/conferences/preprints
[f]Free Access28%○≥80% are freely accessible
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[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18838622
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]47%✗≥60% of references from 2025–2026. Current: 47%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (19 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

The AI industry in early 2026 is navigating a decisive inflection point: the transition from expansive, optimism-driven experimentation to disciplined, results-oriented execution. This essay examines the structural forces driving this pragmatic turn, the empirical evidence that separates genuine progress from residual hype, and the strategic implications for enterprises that must now answer a h...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18838622 26stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted22%○≥80% from verified, high-quality sources
[a]DOI11%○≥80% have a Digital Object Identifier
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[l]Academic11%○≥80% from journals/conferences/preprints
[f]Free Access28%○≥80% are freely accessible
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[w]Words [REQ]1,967✗Minimum 2,000 words for a full research article. Current: 1,967
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18838622
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]47%✗≥60% of references from 2025–2026. Current: 47%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (19 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
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World Models: The Next AI Paradigm — Morning Review 2026-03-02

Posted on March 2, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18829069  40stabilfr·wdophcgmx
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[t]Trusted43%○≥80% from verified, high-quality sources
[a]DOI14%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic29%○≥80% from journals/conferences/preprints
[f]Free Access36%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,298✓Minimum 2,000 words for a full research article. Current: 2,298
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18829069
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]40%✗≥60% of references from 2025–2026. Current: 40%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (32 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

The artificial intelligence landscape is experiencing what may be its most consequential architectural inflection point since the transformer revolution of 2017. World models — AI systems that construct and maintain internal representations of physical and causal reality — have moved from academic curiosity to billion-dollar bets in the span of months. This morning review examines the theoretic...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18829069 40stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources7%○≥80% from editorially reviewed sources
[t]Trusted43%○≥80% from verified, high-quality sources
[a]DOI14%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic29%○≥80% from journals/conferences/preprints
[f]Free Access36%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,298✓Minimum 2,000 words for a full research article. Current: 2,298
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18829069
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]40%✗≥60% of references from 2025–2026. Current: 40%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (32 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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The Planning Illusion

Posted on March 1, 2026March 6, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18824558  41stabilfr·wdophcgmx
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[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed50%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]3,148✓Minimum 2,000 words for a full research article. Current: 3,148
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18824558
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]20%✗≥60% of references from 2025–2026. Current: 20%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (34 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

In my previous essay, "AI is not like us?", I argued that we systematically anthropomorphize AI systems — projecting human cognition onto what are, at their core, profoundly alien statistical machines. That argument was architectural and perceptual. This one is operational.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18824558 41stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
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[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
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[i]Indexed50%○≥80% have metadata indexed
[l]Academic13%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]3,148✓Minimum 2,000 words for a full research article. Current: 3,148
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18824558
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]20%✗≥60% of references from 2025–2026. Current: 20%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (34 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI is not like us?

Posted on March 1, 2026March 1, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18824472  48stabilfr·wdophcgmx
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[t]Trusted65%○≥80% from verified, high-quality sources
[a]DOI19%○≥80% have a Digital Object Identifier
[b]CrossRef15%○≥80% indexed in CrossRef
[i]Indexed42%○≥80% have metadata indexed
[l]Academic46%○≥80% from journals/conferences/preprints
[f]Free Access54%○≥80% are freely accessible
[r]References26 refs✓Minimum 10 references required
[w]Words [REQ]2,938✓Minimum 2,000 words for a full research article. Current: 2,938
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18824472
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]4%✗≥60% of references from 2025–2026. Current: 4%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (46 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

When Alan Turing proposed his famous imitation game in 1950, he embedded a premise so deep we rarely surface it: that intelligence, to be valid, must be indistinguishable from human intelligence. Turing, 1950 — Computing Machinery and Intelligence. The test was never about capability. It was about resemblance.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18824472 48stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources12%○≥80% from editorially reviewed sources
[t]Trusted65%○≥80% from verified, high-quality sources
[a]DOI19%○≥80% have a Digital Object Identifier
[b]CrossRef15%○≥80% indexed in CrossRef
[i]Indexed42%○≥80% have metadata indexed
[l]Academic46%○≥80% from journals/conferences/preprints
[f]Free Access54%○≥80% are freely accessible
[r]References26 refs✓Minimum 10 references required
[w]Words [REQ]2,938✓Minimum 2,000 words for a full research article. Current: 2,938
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18824472
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]4%✗≥60% of references from 2025–2026. Current: 4%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams4✓Mermaid architecture/flow diagrams. Current: 4
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (46 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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Daily Journal: The 95% Crisis — When AI Pilots Can’t Cross the Production Chasm

Posted on February 28, 2026March 1, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18818387  21stabilfr·wdophcgmx
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[t]Trusted7%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed7%○≥80% have metadata indexed
[l]Academic7%○≥80% from journals/conferences/preprints
[f]Free Access21%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]793✗Minimum 2,000 words for a full research article. Current: 793
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18818387
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (11 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)

February 28, 2026 — The AI industry faces a bifurcation point. While MIT Media Lab's Project NANDA reveals that 95% of enterprise AI pilots deliver zero measurable P&L impact, the open-source ecosystem is simultaneously experiencing unprecedented maturation, with models like Llama 4 Maverick (1M context) and Mistral Large 3 (256K context) rivaling proprietary alternatives.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18818387 21stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted7%○≥80% from verified, high-quality sources
[a]DOI7%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed7%○≥80% have metadata indexed
[l]Academic7%○≥80% from journals/conferences/preprints
[f]Free Access21%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]793✗Minimum 2,000 words for a full research article. Current: 793
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18818387
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (11 × 60%) + Required (2/5 × 30%) + Optional (1/4 × 10%)
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AI Agents Operate With Minimal Safety Disclosures: MIT Study Reveals Transparency Gap

Posted on February 23, 2026February 23, 2026 by
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18741627  34stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed17%○≥80% have metadata indexed
[l]Academic17%○≥80% from journals/conferences/preprints
[f]Free Access42%○≥80% are freely accessible
[r]References12 refs✓Minimum 10 references required
[w]Words [REQ]3,130✓Minimum 2,000 words for a full research article. Current: 3,130
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18741627
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]31%✗≥60% of references from 2025–2026. Current: 31%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (23 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

MIT CSAIL's 2025 AI Agent Index analyzed 30 prominent AI agents and found a striking transparency deficit: while 70% provide documentation and nearly half publish code, only 19% disclose formal safety policies and fewer than 10% report external safety evaluations. This journal entry examines the study's findings, contextualizes the claims within the broader AI safety discourse, and assesses whe...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18741627 34stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI8%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed17%○≥80% have metadata indexed
[l]Academic17%○≥80% from journals/conferences/preprints
[f]Free Access42%○≥80% are freely accessible
[r]References12 refs✓Minimum 10 references required
[w]Words [REQ]3,130✓Minimum 2,000 words for a full research article. Current: 3,130
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18741627
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]31%✗≥60% of references from 2025–2026. Current: 31%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (23 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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When AI Finally Beats the Experts: DeepRare and the End of the Diagnostic Odyssey

Posted on February 22, 2026February 22, 2026 by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18730582  49stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources36%○≥80% from editorially reviewed sources
[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI36%○≥80% have a Digital Object Identifier
[b]CrossRef29%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic57%○≥80% from journals/conferences/preprints
[f]Free Access21%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,263✓Minimum 2,000 words for a full research article. Current: 2,263
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18730582
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]27%✗≥60% of references from 2025–2026. Current: 27%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (47 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

A new AI system published in Nature has achieved what many thought impossible: diagnosing rare diseases more accurately than experienced physicians. DeepRare, developed by researchers led by Zhao et al., demonstrates 64.4% top-1 diagnostic accuracy compared to 54.6% for human experts with over a decade of clinical experience. Tested across 6,401 cases spanning 2,919 diseases, the system provide...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18730582 49stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources36%○≥80% from editorially reviewed sources
[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI36%○≥80% have a Digital Object Identifier
[b]CrossRef29%○≥80% indexed in CrossRef
[i]Indexed29%○≥80% have metadata indexed
[l]Academic57%○≥80% from journals/conferences/preprints
[f]Free Access21%○≥80% are freely accessible
[r]References14 refs✓Minimum 10 references required
[w]Words [REQ]2,263✓Minimum 2,000 words for a full research article. Current: 2,263
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18730582
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]27%✗≥60% of references from 2025–2026. Current: 27%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams5✓Mermaid architecture/flow diagrams. Current: 5
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (47 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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The Cognitive Shift: A Creative Vision of How AI Will Change the Way We Think and Perceive

Posted on February 18, 2026February 24, 2026 by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18685239  57stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources33%○≥80% from editorially reviewed sources
[t]Trusted86%✓≥80% from verified, high-quality sources
[a]DOI43%○≥80% have a Digital Object Identifier
[b]CrossRef38%○≥80% indexed in CrossRef
[i]Indexed48%○≥80% have metadata indexed
[l]Academic43%○≥80% from journals/conferences/preprints
[f]Free Access48%○≥80% are freely accessible
[r]References21 refs✓Minimum 10 references required
[w]Words [REQ]6,109✓Minimum 2,000 words for a full research article. Current: 6,109
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18685239
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]0%✗≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (61 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Artificial intelligence is not primarily a threat to human labour — it is a repricing of human cognition. Drawing on Jürgen Schmidhuber's formal theory of intelligence as compression, Robert Sheckley's satirical science fiction, and Isaac Asimov's prescient design specifications for autonomous systems, this essay argues that AI is catalysing the most significant cognitive economy shift since th...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18685239 57stabilfr·wdophcgmx
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (61 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Transforming Science: Math, Biology, and Discovery 2025

Posted on February 2, 2026February 25, 2026 by Admin
Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18748877  35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources13%○≥80% from editorially reviewed sources
[t]Trusted25%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed25%○≥80% have metadata indexed
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[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
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2025 marked a watershed year for AI-driven scientific discovery, with systems transitioning from computational tools to active research partners. Google DeepMind's AlphaEvolve discovered novel algorithms for fundamental mathematical and computational problems, improving efficiency across Google's infrastructure by 0.7% globally and finding new solutions to open problems that have challenged mat...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18748877 35stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources13%○≥80% from editorially reviewed sources
[t]Trusted25%○≥80% from verified, high-quality sources
[a]DOI13%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed25%○≥80% have metadata indexed
[l]Academic25%○≥80% from journals/conferences/preprints
[f]Free Access38%○≥80% are freely accessible
[r]References8 refs○Minimum 10 references required
[w]Words [REQ]2,997✓Minimum 2,000 words for a full research article. Current: 2,997
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18748877
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]25%✗≥60% of references from 2025–2026. Current: 25%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (24 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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