
Episode #7
PS2002 - 11 - Consciousness
<p>Dr Hannah Thompson's lecture about consciousness</p><br /><br />This podcast has been generated automatically and contains some inaccuracies.

Loading…

education
Hosted by Ansgar Endress · education · EN-US · 12 episodes
This podcast is based on lectures by Dr. Ansgar Endress, summarized using NotebookLM for an accessible overview. However, please be aware that all episodes contain (minor) inaccuracies. For the most accurate information, please watch the original lectures.
Required Pod Score for this show. PitchCentric checks your profile against host openness, topical fit, and audience signals before you generate a pitch.
Contact path
Verified email
Booking probability
19%
Guest openness
Selective
Sign up to generate a grounded pitch for Ansgar's lectures.
Signup to Generate a PitchAnsgar's lectures is a education podcast hosted by Ansgar Endress, with 12 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.
Ansgar Endress hosts Ansgar's lectures, a education show with 12 episodes published.
Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

Episode #7
<p>Dr Hannah Thompson's lecture about consciousness</p><br /><br />This podcast has been generated automatically and contains some inaccuracies.

Episode #6
<p>Note that this is an automatically generated podcast containing some inaccuracies.</p><p>This lecture examines the large number system in humans and animals, highlighting Weber's Law as a driving principle. The discussion covers experimental evidence for this law in number discrimination and estimation, and proposes that it arises from the brain's limited precision when representing a wide range of quantities. Furthermore, the lecture explores individual differences in large number processing, demonstrating a correlation between Weber ratios and mathematical performance.</p><br /><br />This podcast has been generated automatically and contains some inaccuracies.

Episode #5
<p>Note that this is an automatically generated podcast containing some inaccuracies.</p><p>This lecture explores specialized cognitive mechanisms for number processing, distinguishing between a small number system for quantities up to three or four, which allows for immediate and precise recognition without counting, and a large number system for greater quantities, characterized by approximate representations governed by Weber's Law, where discriminability depends on the relative difference between quantities.</p><br /><br />This podcast has been generated automatically and contains some inaccuracies.

Episode #4
<p>Podcast episode by Dr. Hannah Thompson's lecture about concepts and knowledge representation</p><br /><br />This podcast has been generated automatically and contains some inaccuracies.

Episode #3
<p>Note that this is an automatically generated podcast containing some inaccuracies.</p><p><br></p><p>This lecture explores mechanisms underlying word learning, focusing on further learning constraints. It highlights the taxonomic constraint, where learners assume new words refer to categories, often at the basic level. However, verbal cues also allow them to consider more abstract categories. We further examine the challenges of verb learning, arguing that grammatical context is a crucial source of information, enabling learners to infer the meaning of verbs based on their syntactic context.</p><br /><br />This podcast has been generated automatically and contains...
Recent guests on Ansgar's lectures. Study who booked and why before you pitch.
Sponsor detection runs nightly. Check back soon.
Based on semantic analysis of episode topics and host coverage, this show is a strong guest fit for executives in:
Industry fit is computed by PitchCentric using vector embeddings of the show's episode catalog.
Is this podcast yours and you'd like to remove or correct details? Request removal or email privacy@pitchcentric.com.
FAQs
If you have a concern about deliverability, AI quality, data privacy, or whether this will actually work for your specific situation, it's probably answered below.
Founder Solo gives you 50 AI pitches per month using the credit model (Standard pitches cost 1 credit, Enriched pitches cost 2). Founder Pro raises that to 200 credits per month and adds full Booking Probability access, unlimited Magic Match, Apollo enrichment credits, and data export capabilities. Both plans use the same credit system, so you can stretch your monthly budget further by using Standard-mode drafting.
Agency tiers have no base fee. You pay per managed client and per talent profile. Agency Standard is $199 per client per month; Agency Pro is $399 per client per month. Both add $39 per talent profile per month. Your own team's user seats are always free.
A talent profile represents one person (founder, executive, or spokesperson) you are booking onto podcasts. It includes their bio, topics, headshots, and outreach history. Team plans include 5 profiles; agency plans are pay-as-you-go.
Yes, at any time. Upgrades take effect immediately; downgrades apply at the end of the current billing period. Contact support if you need help migrating between plan families.
Every paid plan includes a 15-day free trial. Your card is saved at signup but you will not be charged until day 16. Cancel any time from your dashboard.
You keep access until the end of your current billing period. No charges after that. Your data is retained for 30 days in case you reactivate.
Yes. Select Annual on the pricing toggle and the discounted price is applied automatically at checkout. The annual price shown is the full year cost.
That is our Enterprise tier. Contact our sales team and we will build a custom plan with volume pricing, a dedicated account manager, and SLA guarantees.