Hire Now
Message Daniel
Languages
English
Hebrew
Jobs Completed
1
Usually responds
Within a few hours
See how it works
Book Daniel with Paydesk
Make your booking securely through paydesk for these benefits:
1
Preferred Booking Channel
Daniel is more likely to commit to assignments booked through paydesk, as it is a trusted platform that validates the seriousness and legitimacy of each engagement.2
Insured Bookings for Peace of Mind
We provide basic insurance coverage with each booking on paydesk, giving both you and the media professional confidence and protection while they work for you.3
Effortless Online Payment
Paydesk offers a payment protection system to ensure payments are only finalized when you are satisfied with the job completion. Freelancers trusts our process that guarantees their efforts are rewarded upon successful delivery of servicesStill have questions?
Check FAQAbout Daniel
Daniel Bear is a journalist based in Be'er Sheva, Israel. Photographer and Videographer specializing in outdoor and documentary Projects. Fluent in Hebrew and English and can be used as a translator, Fixer or Field Producer for Various Projects. Licensed Drone Operator.
Portfolio
What should THC limit be for cannabis edibles in Canada?
The debate in Canada centers around the current 10 mg THC limit per package of cannabis edibles. Public health professionals resist industry calls to increase this limit, while the Cannabis Council of Canada suggests a 100 mg limit, aligning with California's laws. Research indicates that infrequent consumers feel effects at low doses, raising concerns about overconsumption and child safety. However, higher limits could reduce prices, encouraging legal market transition and offering harm reduction through child-proof packaging and public education. The author leans towards increasing the limit to 100 mg, with the possibility of future increases after evaluation.
Five years of cannabis legalization: What needs to change?
Five years after Canada legalized recreational cannabis, the policy's success is under review. The legal market faces challenges such as overproduction, environmental concerns, and lack of representation for marginalized communities. Comparisons with California's approach and Quebec's centralized model offer insights. The series aims to chart a path toward a sustainable and equitable cannabis market that prioritizes health and safety.
A tale of two cannabis legalization experiments
Five years after Canada legalized non-medical cannabis, both Canada and California face challenges despite different regulatory approaches. Canada's federal legislation provides stability, but high taxes and strict regulations hinder market access and profitability. California's industry struggles with federal prohibition, high taxes, and local resistance, sustaining an illicit market. Both regions need to prioritize social equity, recalibrate tax structures, and consider non-profit models to create a viable and just cannabis industry. Removing cannabis from the U.S. list of prohibited drugs is crucial for market success.
A tale of two cannabis legalization experiments
Canada and California, both pioneers in cannabis legalization, face similar challenges despite different regulatory approaches. Canada's federal legislation provides stability, but high taxes and strict regulations hinder market growth. California's industry struggles with federal prohibition, high taxes, and local resistance, sustaining an illicit market. Both regions need to prioritize social equity, recalibrate tax structures, and consider non-profit models to address production and retail challenges. Removing cannabis from the U.S. list of prohibited drugs is crucial for market success.
Here's what happened when researchers raised monkeys who never saw a face
Researchers at Harvard Medical School conducted a study on macaque monkeys raised without exposure to faces to understand the development of face patches in the brain. The study found that face patches did not develop in face-deprived monkeys, suggesting that visual experience with faces is necessary for their formation. This challenges the notion that face recognition abilities are innate and highlights the role of environmental stimuli in cognitive development. The findings contribute to the ongoing nature vs. nurture debate, indicating that while genetic predispositions exist, sensory experiences significantly shape neural structures.
How machine learning is helping us to understand the brain
The article discusses how traditional models of understanding the brain, based on signal processing and information theory, are being replaced by insights from machine learning. It argues that the brain's complex functions are better explained through evolutionary principles and machine learning algorithms, which, like evolution, improve through small, incremental steps. The article highlights the limitations of previous models and suggests that machine learning offers a more accurate framework for understanding neural processes.
How Artificial Intelligence Can Explain Unconscious Decision-Making
Artificial intelligence (AI) offers insights into unconscious decision-making processes that are often more accurate than human verbal explanations. While humans tend to provide post-hoc rationalizations for their actions, AI algorithms can reveal the true computational processes behind decisions. This understanding challenges the traditional notion of 'explanation' and emphasizes the importance of mathematical descriptions over verbal reports. AI's transparency in its decision-making process, despite being labeled as 'black boxes,' can help address biases and improve decision-making in various fields, including driving and medical diagnostics.
Artificial intelligence isn't a 'black box.' It's a key to studying the brain
Artificial intelligence (AI) offers a mathematical approach to understanding brain computations, challenging the traditional verbal explanations of human behavior. While human explanations for actions are often unreliable, AI algorithms provide transparent, data-driven insights. The article argues that AI should not be seen as a 'black box' but as a tool for uncovering the unconscious processes that govern both machine and human decision-making. It emphasizes the need for precise, algorithmic descriptions over simplistic language-level explanations to truly understand and improve AI and human cognition.
How machine learning is helping neuroscientists understand the brain
The article discusses how traditional metaphors and models in neuroscience, which are based on signal processing and information theory, are insufficient for understanding the brain's complexities. It argues that machine learning, which mirrors the evolutionary process of natural selection, offers a more accurate framework for studying brain functions. The piece highlights the limitations of previous models and suggests that the principles of machine learning, which involve iterative improvement and flexibility, align more closely with how the brain operates. This new approach could lead to better explanations and models of neural behavior.
How machine learning is helping neuroscientists understand the brain
The article discusses the limitations of traditional neuroscience models based on signal processing and information theory, advocating for a shift towards machine learning metaphors to better understand brain function. It highlights the parallels between evolutionary processes and machine learning algorithms, emphasizing the need for computational principles that align with the brain's evolutionary design. The text argues that while traditional models have provided some insights, machine learning offers a more flexible and effective framework for explaining complex neural phenomena.
Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium
doloremque laudantium,
totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur?
doloremque laudantium,
totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae dicta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur?
Want to see more portfolio samples?
Sign up to paydesk, it’s free!
Log In
Sign Up
×
Daniel's
confirmed information
✓
Identity
Verified using government ID
Nov 2023
Nov 2023
✓
Financial institution
Verified Nov 2023
✓
Phone number
Verified Nov 2023
✓
Joined
Nov 2023